4,264 Data Engineering Manager jobs in India
Data Engineering Manager
Posted today
Job Viewed
Job Description
We are an organisation that exists to drive progress. That's the "red thread" that connects everyone at The Economist Group (TEG). Our businesses share a devotion to innovation, independence and rigour in their fields of expertise. We empower people to understand and tackle the critical challenges and changes facing the world. Our analytical rigour, global expertise and evidence-based insights enable individuals and organisations to make sense of these shifts and chart a course through them.
We deliver analysis and insights in many formats to subscribers and clients in 170 countries through our four businesses, The Economist, Economist Impact, Economist Intelligence and Economist Education, which uphold our global reputation for excellence and integrity.
We are recruiting for a technically strong, people-centric Data Engineering Manager to lead a high-impact AI & Data engineering team based in India. This group will build the data platform and products to support the analytics, insights and data science needs for our core subscription business. Data has always been at the heart of the Economist Group, and ultimately we aim to help the business make data driven judgements based on real time, actionable insights
How you will contribute in this role:
- Work with data product managers, analysts, and data scientists to build data and ML pipelines, data warehouse/data lake-house for analytics, reporting and prediction.
- Build pipelines and data lake house/warehouse with data feeds/APIs using Lakehouse, Snowflake, Apache Airflow, Amazon EMR on Snowflake and AWS data lake house.
- Work with data quality and observability tools, CI/CD frameworks to maintain data engineering excellence.
- Work on data modelling, lineage and data governance
- Manage and support a team of engineers through regular 1:1s, coaching, performance feedback, and career development. Foster an inclusive, growth-oriented team culture
- Contribute to engineering strategy and practices. Shape processes, team rituals, and tooling that enable your team to deliver high-quality code efficiently and safely
- Take full ownership of systems in your domain, ensuring observability, uptime, performance, documentation, and operational readiness
- Understand the productivity of your teams and the factors affecting productivity and intervening when required
What we're looking for:
- Professional experience of designing, building data pipelines and managing data platforms (including ETL, ELT and lambda architectures), using technologies such as Apache Airflow, Amazon Athena, AWS Glue, Amazon EMR, or other equivalent.
- Expert level knowledge of both SQL and programming (Python, Scala, or Java)
- Experience with data technologies such as object storage (s3, hdfs), lakehouse (Iceberg or equivalent), data warehousing (Snowflake or equivalent), orchestration (Airflow or equivalent), data processing frameworks (Pyspark, pandas or equivalent) data modelling, lineage and governance tools.
- Professional experience in cloud platforms (AWS strongly preferred), such as serverless functions, API gateway, relational and NoSQL databases, and caching.
- Experience with IaC, CI/CD, containerization, and DevOps.
- Experience in working in teams with data scientists and ML engineers, for building ML pipelines for recommendation, customer lifetime value and propensity models.
- An advanced degree in software / data engineering, computer / information science, or a related quantitative field or equivalent work experience.
- Strong verbal and written communication skills and ability to work well with a wide range of stakeholders.
- Strong ownership, scrappy and biased for action.
#LI-Hybrid
AI usage for your applicationWe are an innovative organisation that encourages the use of technology. We recognise that candidates may utilise AI tools to support with their job application process. However, it is essential that all information you provide truthfully and accurately reflects your own experience, skills, and qualifications.
What we offerOur benefits package is designed to support your wellbeing, growth, and work-life balance. It includes a highly competitive pension or 401(k) plan, private health insurance, and 24/7 access to counselling and wellbeing resources through our Employee Assistance Program.
We also offer a range of lifestyle benefits, including our Work From Anywhere program, which allows you to work from any location where you have the legal right to do so for up to 40 days per year. In addition, we provide generous annual and parental leave, as well as dedicated days off for volunteering and even for moving home.
You will also be given free access to all The Economist content, including an online subscription, our range of apps, podcasts and more.
Data Engineering Manager
Posted today
Job Viewed
Job Description
Role Description:
We are seeking a seasoned Engineering Manager (Data Engineering) to drive the development and implementation of our data strategy with deep expertise in R&D of Biotech or Pharma domain. This role will lead a team of data engineers to build, optimize, and maintain scalable data architectures, data pipelines, and operational frameworks that support real-time analytics, AI-driven insights, and enterprise-wide data solutions.
As a strategic leader, the ideal candidate will drive best practices in data engineering, cloud technologies, and Agile development, ensuring robust governance, data quality, and efficiency. The role requires technical expertise, team leadership, and a deep understanding of cloud data solutions to optimize data-driven decision-making.
Roles & Responsibilities:
- Lead and mentor a team of data engineers, fostering a culture of innovation, collaboration, and continuous learning for solving complex problems of R&D division.
- Oversee the development of data extraction, validation, and transformation techniques, ensuring ingested data is of high quality and compatible with downstream systems.
- Guide the team in writing and validating high-quality code for data ingestion, processing, and transformation, ensuring resiliency and fault tolerance.
- Drive the development of data tools and frameworks for managing and accessing data efficiently across the organization.
- Oversee the implementation of performance monitoring protocols across data pipelines, ensuring real-time visibility, alerts, and automated recovery mechanisms.
- Coach engineers in building dashboards and aggregations to monitor pipeline health and detect inefficiencies, ensuring optimal performance and cost-effectiveness.
- Lead the implementation of self-healing solutions, reducing failure points and improving pipeline stability and efficiency across multiple product features.
- Oversee data governance strategies, ensuring compliance with security policies, regulations, and data accessibility best practices.
- Guide engineers in data modeling, metadata management, and access control, ensuring structured data handling across various business use cases.
- Collaborate with business leaders, product owners, and cross-functional teams to ensure alignment of data architecture with product requirements and business objectives.
- Prepare team members for stakeholder discussions by helping assess data costs, access requirements, dependencies, and availability for business scenarios.
- Drive Agile and Scaled Agile (SAFe) methodologies, managing sprint backlogs, prioritization, and iterative improvements to enhance team velocity and project delivery.
- Stay up-to-date with emerging data technologies, industry trends, and best practices, ensuring the organization leverages the latest innovations in data engineering and architecture.
Functional Skills:
Must-Have Skills:
- Experience managing a team of data engineers in the R&D domain of biotech/pharma companies.
- Experience architecting and building data and analytics solutions that extract, transform, and load data from multiple source systems.
- Data Engineering experience in R&D for Biotechnology or pharma industry
- Demonstrated hands-on experience with cloud platforms (AWS) and the ability to architect cost-effective and scalable data solutions.
- Proficiency in Python, PySpark, SQL.
- Experience with dimensional data modeling.
- Experience working with Apache Spark, Apache Airflow.
- Experienced with software engineering best-practices, including but not limited to version control (Git, Subversion, etc.), CI/CD (Jenkins, Maven etc.), automated unit testing, and Dev Ops.
- Experienced with AWS or GCP or Azure cloud services.
- Understanding of end to end project/product life cycle
- Well versed with full stack development & DataOps automation, logging frameworks, and pipeline orchestration tools.
- Strong analytical and problem-solving skills to address complex data challenges.
- Effective communication and interpersonal skills to collaborate with cross-functional teams.
Good-to-Have Skills:
- Data Engineering Management experience in Biotech/Pharma is a plus
- Experience using graph databases such as Stardog or Marklogic or Neo4J or Allegrograph, etc.
Education and Professional Certifications
- Masters degree with years of experience in Computer Science, IT or related field
- OR
- Bachelors degree with years of experience in Computer Science, IT or related field
- AWS Certified Data Engineer preferred
- Databricks Certificate preferred
- Scaled Agile SAFe certification preferred
- Project Management certifications preferred
Soft Skills:
- Excellent analytical and troubleshooting skills
- Strong verbal and written communication skills
- Ability to work effectively with global, virtual teams
- High degree of initiative and self-motivation
- Ability to manage multiple priorities successfully
- Team-oriented, with a focus on achieving team goals
- Strong presentation and public speaking skills.
Data Engineering Manager
Posted today
Job Viewed
Job Description
Collinson
Collinson is a global loyalty and benefits company.
We use our expertise and products to craft customer experiences which enable some of the world's best known brands to acquire, engage and retain the most demanding and choice-rich customers. In particular, our unique expertise and insight into high earning, frequent travellers allows us to create products and solutions for our clients that inspire greater customer engagement to drive more profitable relationships, enrich their travel experiences, protect what matters and assist in in times of need.
While specialising in Financial Services, Travel and Retail, we also support clients in multiple sectors. We have worked with over 90 airlines, 20 hotel groups and more than 600 financial institutions and banks, with clients including Accor Hotels, Air France KLM, American Express, British Airways, Cathay Pacific, Diners Club, Mandarin Oriental, Mastercard, Radisson Hotel Group, Sephora, Visa and Vhi.
We take our 30 years' experience working with these kinds of household names in over 170 countries, and help our clients to deliver the smarter experiences it takes to differentiate their propositions, and help them win deeper devotion with their customers.
Collinson is a privately-owned entrepreneurial business with 2,000 passionate people working in 20 locations worldwide. Our solutions include Priority Pass, the world's best known airport experiences programme, while we are also the trusted partner behind many of the leading financial services, airline and hotel brand's reward programmes and loyalty initiatives.
Purpose of the job
We are seeking a Data Engineering Manager who is passionate about building great teams, shipping products fast, and fostering an inspiring engineering culture. You'll be the kind of person who loves to see data engineers grow, removes obstacles before they become problems, and knows that the best teams deliver not because of deadlines, but because they're truly engaged in what they're building. You will partner closely with our Principal Data Engineer to ensure a balanced approach across execution excellence, career progression, technical innovation, and delivery discipline.
building.
You'll bring a strong technical background and have been hands-on with data engineering and building data products. You get how engineers think, and how to help them thrive. You believe in iterating fast, learning from failure, and building scalable, maintainable systems without getting bogged down in bureaucracy.
This role requires a leader who is technically credible, but who also thrives on building an empowered, high-performing team. You'll manage and mentor data engineers, align delivery to business needs, and champion both engineering quality and personal development
Key Responsibilities
Leadership & People Management
- Lead, coach, and mentor a team of data engineers, focusing on career growth, learning, and engagement.
- Take ownership of people management, including development plans, performance reviews, and progression pathways.
- Partner with the Principal Data Engineer to balance technical depth with delivery accountability, ensuring the team excels in both.
- Foster a culture of collaboration, inclusion, and innovation within the data engineering function.
Technical Delivery & Execution
- Oversee the design and implementation of scalable, high-quality data pipelines on AWS and Snowflake.
- Collaborate with the Principal Data Engineer on technical architecture and standards, ensuring solutions are future-proof and cost-efficient.
- Drive adoption of best practices in data engineering, CI/CD, and agile delivery.
- Ensure compliance with governance, security, and data quality requirements.
- Continuously optimize data flows to support business analytics, personalization, and advanced data products.
Strategic Influence & Stakeholder Engagement
- Work with Product Owners, Data Governance, and Analytics teams to align engineering work to strategic data goals.
- Communicate progress and solutions effectively to technical and non-technical stakeholders.
- Represent data engineering in cross-functional forums, advocating for modern, reliable, and business-enabling data solutions.
- Contribute to shaping the Data & Analytics roadmap, ensuring scalability for future growth.
Knowledge, skills and experience required
Leadership & People Development
- Proven experience leading and developing high-performing data engineering teams, ideally across hybrid or distributed environments.
- Strong focus on people management — setting clear expectations, supporting individual growth, and ensuring structured career progression.
- Ability to foster a culture of learning, inclusion, and psychological safety, empowering engineers to innovate and take ownership.
- Skilled in coaching engineers of varying experience levels, providing both technical mentorship and constructive feedback.
- Experience partnering with a Principal Data Engineer or equivalent to maintain balance between technical excellence and delivery execution.
Technical Expertise
- Deep understanding of modern data architecture patterns - Data Lake, Data Warehouse, Lakehouse, and Data Mesh.
- Proven experience designing and delivering cloud data platforms (preferably AWS and Snowflake).
- Expertise in ETL/ELT development, orchestration, and data automation using tools such as AWS Glue, Step Functions, Airflow, or dbt.
- Strong programming proficiency in Python and SQL, with experience in testing, optimisation, and CI/CD integration.
- Experience with streaming and event-driven architectures (e.g., Kafka, Kinesis).
- Knowledge of infrastructure-as-code (Terraform, CloudFormation) and data observability best practices.
- Strong background in data modelling (dimensional, canonical, and semantic models) to support analytical and operational use cases.
- Understanding of data governance, security, and privacy principles, including GDPR compliance, data lineage, and access controls.
Delivery & Execution
- Demonstrated success delivering data solutions using Agile methodologies (Scrum/Kanban).
- Skilled at balancing speed, quality, and cost, with awareness of cloud resource efficiency and cost management.
- Experienced in leading both strategic transformation projects (platform migrations, architecture redesigns) and incremental delivery improvements (pipeline tuning, automation).
- Confident in aligning technical delivery with business needs and collaborating closely with Product, Analytics, and Governance teams.
- Strategic & Communication Skills
- Excellent communicator — able to explain complex technical solutions in clear, accessible language.
- Strong influencing skills to drive adoption of modern data practices and data-driven decision-making across the business.
- Strategic thinker who connects engineering initiatives with business value, supporting innovation and scalability.
- High accountability, resilience, and adaptability in a fast-moving environment.
Data Engineering manager
Posted 3 days ago
Job Viewed
Job Description
Who We Are:
Ever wonder who brings the entertainment to your flights? Panasonic Avionics Corporation is #1 in the industry for delivering inflight products such as movies, games, WiFi, and now Bluetooth headphone connectivity!
How exciting would it be to be a part of the innovation that goes into creating technology that delights millions of people in an industry that's here to stay! With our company's history spanning over 40 years, you will have stability, career growth opportunities, and will work with the brightest minds in the industry. And we are committed to a diverse and inclusive culture that will help our organization thrive! We seek diversity in many areas such as background, culture, gender, ways of thinking, skills and more.
If you want to learn more about us visit us at ( . And for a full listing of open job opportunities go to (
**The Position:**
We are seeking a proven Data Engineering Leader to drive the design, development, and deployment of scalable, secure, and high-performance data solutions. This role will lead high-performing teams, architect cloud-native data platforms, and collaborate closely with business, AI/ML, and BI teams to deliver end-to-end data products that power innovation and strategic decision-making.
The position offers the opportunity to shape data architecture strategy, establish best practices in Lakehouse and streaming solutions, and enable advanced analytics and AI/ML at scale.
**Responsibilities**
**What We're Looking For:**
+ Proven leadership in building and mentoring high-performing data engineering teams.
+ Expertise in architecting cloud-native data platforms on AWS, leveraging services such as EMR, EKS, Glue, Redshift, S3, Lambda, and SageMaker.
+ Strong background in Lakehouse architecture (Glue Catalog, Iceberg, Delta Lake) and distributed processing frameworks (Spark, Hive, Presto).
+ Experience with real-time streaming solutions (Kafka, Kinesis, Flink).
+ Proficiency in orchestrating complex data workflows with Apache Airflow.
+ Hands-on experience with GitLab CI/CD, Terraform, CloudFormation Templates, and Infrastructure-as-Code.
+ Strong understanding of MDM strategies and data governance best practices (GDPR, HIPAA, etc.).
+ Ability to design and develop middleware APIs (REST) to seamlessly integrate data pipelines with applications and analytics platforms.
+ Experience supporting AI/ML teams with feature engineering, training, and deployment pipelines using SageMaker.
+ Solid knowledge of SQL & NoSQL databases (Redshift, DynamoDB, PostgreSQL, Elasticsearch).
+ Familiarity with BI enablement and data modeling for visualization platforms like Amazon QuickSight.
+ In-depth knowledge of security best practices in AWS-based data architectures.
+ Demonstrated success in driving AI/ML initiatives from ideation to production.
**Our Principles:** ** **
Contribution to Society | Fairness & Honesty | Cooperation & Team Spirit | Untiring Effort for Improvement | Courtesy & Humility | Adaptability | Gratitude
**What We Offer:** ** **
At Panasonic Avionics Corporation we realize the most important aspects in leading our industry are the bright minds behind everything we do. We are proud to offer our employees a highly competitive, comprehensive and flexible benefits program.
**Qualifications**
**Educational Background:**
+ Bachelor's degree or higher in Computer Science, Data Engineering, Aerospace Engineering, or a related field.
+ Advanced degrees (Master's/PhD) in Data Science or AI/ML are a plus.
REQ-
Data Engineering Manager
Posted 3 days ago
Job Viewed
Job Description
Amgen harnesses the best of biology and technology to fight the world's toughest diseases, and make people's lives easier, fuller and longer. We discover, develop, manufacture and deliver innovative medicines to help millions of patients. Amgen helped establish the biotechnology industry more than 40 years ago and remains on the cutting-edge of innovation, using technology and human genetic data to push beyond what's known today.
**ABOUT THE ROLE**
**Role Description:**
We are seeking a seasoned Engineering Manager (Data Engineering) to drive the development and implementation of our data strategy with deep expertise in R&D of Biotech or Pharma domain. This role will lead a team of data engineers to build, optimize, and maintain scalable data architectures, data pipelines, and operational frameworks that support real-time analytics, AI-driven insights, and enterprise-wide data solutions. As a strategic leader, the ideal candidate will drive best practices in data engineering, cloud technologies, and Agile development, ensuring robust governance, data quality, and efficiency. The role requires technical expertise, team leadership, and a deep understanding of cloud data solutions to optimize data-driven decision-making.
**Roles & Responsibilities:**
+ Lead and mentor a team of data engineers, fostering a culture of innovation, collaboration, and continuous learning for solving complex problems of R&D division.
+ Oversee the development of data extraction, validation, and transformation techniques, ensuring ingested data is of high quality and compatible with downstream systems.
+ Guide the team in writing and validating high-quality code for data ingestion, processing, and transformation, ensuring resiliency and fault tolerance.
+ Drive the development of data tools and frameworks for managing and accessing data efficiently across the organization.
+ Oversee the implementation of performance monitoring protocols across data pipelines, ensuring real-time visibility, alerts, and automated recovery mechanisms.
+ Coach engineers in building dashboards and aggregations to monitor pipeline health and detect inefficiencies, ensuring optimal performance and cost-effectiveness.
+ Lead the implementation of self-healing solutions, reducing failure points and improving pipeline stability and efficiency across multiple product features.
+ Oversee data governance strategies, ensuring compliance with security policies, regulations, and data accessibility best practices.
+ Guide engineers in data modeling, metadata management, and access control, ensuring structured data handling across various business use cases.
+ Collaborate with business leaders, product owners, and cross-functional teams to ensure alignment of data architecture with product requirements and business objectives.
+ Prepare team members for stakeholder discussions by helping assess data costs, access requirements, dependencies, and availability for business scenarios.
+ Drive Agile and Scaled Agile (SAFe) methodologies, managing sprint backlogs, prioritization, and iterative improvements to enhance team velocity and project delivery.
+ Stay up-to-date with emerging data technologies, industry trends, and best practices, ensuring the organization leverages the latest innovations in data engineering and architecture.
**Functional Skills:**
**Must-Have Skills:**
+ Experience managing a team of data engineers in the R&D domain of biotech/pharma companies.
+ Experience architecting and building data and analytics solutions that extract, transform, and load data from multiple source systems.
+ Data Engineering experience in R&D for Biotechnology or pharma industry
+ Demonstrated hands-on experience with cloud platforms (AWS) and the ability to architect cost-effective and scalable data solutions.
+ Proficiency in Python, PySpark, SQL.
+ Experience with dimensional data modeling.
+ Experience working with Apache Spark, Apache Airflow.
+ Experienced with software engineering best-practices, including but not limited to version control (Git, Subversion, etc.), CI/CD (Jenkins, Maven etc.), automated unit testing, and Dev Ops.
+ Experienced with AWS or GCP or Azure cloud services.
+ Understanding of end to end project/product life cycle
+ Well versed with full stack development & DataOps automation, logging frameworks, and pipeline orchestration tools.
+ Strong analytical and problem-solving skills to address complex data challenges.
+ Effective communication and interpersonal skills to collaborate with cross-functional teams.
**Good-to-Have Skills:**
+ Data Engineering Management experience in Biotech/Pharma is a plus
+ Experience using graph databases such as Stardog or Marklogic or Neo4J or Allegrograph, etc.
**Education and Professional Certifications**
+ Master's degree with 10 - 12 + years of experience in Computer Science, IT or related field
+ OR
+ Bachelor's degree with 8 -10 + years of experience in Computer Science, IT or related field
+ AWS Certified Data Engineer preferred
+ Databricks Certificate preferred
+ Scaled Agile SAFe certification preferred
+ Project Management certifications preferred
**Soft Skills:**
+ Excellent analytical and troubleshooting skills
+ Strong verbal and written communication skills
+ Ability to work effectively with global, virtual teams
+ High degree of initiative and self-motivation
+ Ability to manage multiple priorities successfully
+ Team-oriented, with a focus on achieving team goals
+ Strong presentation and public speaking skills
**EQUAL OPPORTUNITY STATEMENT**
Amgen is an Equal Opportunity employer and will consider you without regard to your race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or disability status. We will ensure that individuals with disabilities are provided with reasonable accommodation to participate in the job application or interview process, to perform essential job
Data Engineering Manager
Posted 3 days ago
Job Viewed
Job Description
Amgen harnesses the best of biology and technology to fight the world's toughest diseases, and make people's lives easier, fuller and longer. We discover, develop, manufacture and deliver innovative medicines to help millions of patients. Amgen helped establish the biotechnology industry more than 40 years ago and remains on the cutting-edge of innovation, using technology and human genetic data to push beyond what's known today.
**ABOUT THE ROLE**
**Role Description:**
We are seeking a seasoned Engineering Manager (Data Engineering) to lead the end-to-end management of enterprise data assets and operational data workflows. This role is critical in ensuring the availability, quality, consistency, and timeliness of data across platforms and functions, supporting analytics, reporting, compliance, and digital transformation initiatives. You will be responsible for the day-to-day data operations, manage a team of data professionals, and drive process excellence in data intake, transformation, validation, and delivery. You will work closely with cross-functional teams including data engineering, analytics, IT, governance, and business stakeholders to align operational data capabilities with enterprise needs.
**Roles & Responsibilities:**
+ Lead and manage the enterprise data operations team, responsible for data ingestion, processing, validation, quality control, and publishing to various downstream systems.
+ Define and implement standard operating procedures for data lifecycle management, ensuring accuracy, completeness, and integrity of critical data assets.
+ Oversee and continuously improve daily operational workflows, including scheduling, monitoring, and troubleshooting data jobs across cloud and on-premise environments.
+ Establish and track key data operations metrics (SLAs, throughput, latency, data quality, incident resolution) and drive continuous improvements.
+ Partner with data engineering and platform teams to optimize pipelines, support new data integrations, and ensure scalability and resilience of operational data flows.
+ Collaborate with data governance, compliance, and security teams to maintain regulatory compliance, data privacy, and access controls.
+ Serve as the primary escalation point for data incidents and outages, ensuring rapid response and root cause analysis.
+ Build strong relationships with business and analytics teams to understand data consumption patterns, prioritize operational needs, and align with business objectives.
+ Drive adoption of best practices for documentation, metadata, lineage, and change management across data operations processes.
+ Mentor and develop a high-performing team of data operations analysts and leads.
**Functional Skills:**
**Must-Have Skills:**
+ Experience managing a team of data engineers in biotech/pharma domain companies.
+ Experience in designing and maintaining data pipelines and analytics solutions that extract, transform, and load data from multiple source systems.
+ Demonstrated hands-on experience with cloud platforms (AWS) and the ability to architect cost-effective and scalable data solutions.
+ Experience managing data workflows in cloud environments such as AWS, Azure, or GCP.
+ Strong problem-solving skills with the ability to analyze complex data flow issues and implement sustainable solutions.
+ Working knowledge of SQL, Python, or scripting languages for process monitoring and automation.
+ Experience collaborating with data engineering, analytics, IT operations, and business teams in a matrixed organization.
+ Familiarity with data governance, metadata management, access control, and regulatory requirements (e.g., GDPR, HIPAA, SOX).
+ Excellent leadership, communication, and stakeholder engagement skills.
+ Well versed with full stack development & DataOps automation, logging frameworks, and pipeline orchestration tools.
+ Strong analytical and problem-solving skills to address complex data challenges.
+ Effective communication and interpersonal skills to collaborate with cross-functional teams.
**Good-to-Have Skills:**
+ Data Engineering Management experience in Biotech/Life Sciences/Pharma
+ Experience using graph databases such as Stardog or Marklogic or Neo4J or Allegrograph, etc.
**Education and Professional Certifications**
+ Doctorate Degree with 3-5 + years of experience in Computer Science, IT or related field
+ OR
+ Master's degree with 6 - 8 + years of experience in Computer Science, IT or related field
+ OR
+ Bachelor's degree with 10 - 12 + years of experience in Computer Science, IT or related field
+ AWS Certified Data Engineer preferred
+ Databricks Certificate preferred
+ Scaled Agile SAFe certification preferred
**Soft Skills:**
+ Excellent analytical and troubleshooting skills
+ Strong verbal and written communication skills
+ Ability to work effectively with global, virtual teams
+ High degree of initiative and self-motivation
+ Ability to manage multiple priorities successfully
+ Team-oriented, with a focus on achieving team goals
+ Strong presentation and public speaking skills
**EQUAL OPPORTUNITY STATEMENT**
Amgen is an Equal Opportunity employer and will consider you without regard to your race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or disability status. We will ensure that individuals with disabilities are provided with reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request an accommodation.
Data Engineering Manager
Posted 3 days ago
Job Viewed
Job Description
Amgen harnesses the best of biology and technology to fight the world's toughest diseases, and make people's lives easier, fuller and longer. We discover, develop, manufacture and deliver innovative medicines to help millions of patients. Amgen helped establish the biotechnology industry more than 40 years ago and remains on the cutting-edge of innovation, using technology and human genetic data to push beyond what's known today.
**ABOUT THE ROLE**
**Role Description:**
We are seeking a seasoned Engineering Manager (Data Engineering) to lead the end-to-end management of enterprise data assets and operational data workflows. This role is critical in ensuring the availability, quality, consistency, and timeliness of data across platforms and functions, supporting analytics, reporting, compliance, and digital transformation initiatives. You will be responsible for the day-to-day data operations, manage a team of data professionals, and drive process excellence in data intake, transformation, validation, and delivery. You will work closely with cross-functional teams including data engineering, analytics, IT, governance, and business stakeholders to align operational data capabilities with enterprise needs.
**Roles & Responsibilities:**
+ Lead and manage the enterprise data operations team, responsible for data ingestion, processing, validation, quality control, and publishing to various downstream systems.
+ Define and implement standard operating procedures for data lifecycle management, ensuring accuracy, completeness, and integrity of critical data assets.
+ Oversee and continuously improve daily operational workflows, including scheduling, monitoring, and troubleshooting data jobs across cloud and on-premise environments.
+ Establish and track key data operations metrics (SLAs, throughput, latency, data quality, incident resolution) and drive continuous improvements.
+ Partner with data engineering and platform teams to optimize pipelines, support new data integrations, and ensure scalability and resilience of operational data flows.
+ Collaborate with data governance, compliance, and security teams to maintain regulatory compliance, data privacy, and access controls.
+ Serve as the primary escalation point for data incidents and outages, ensuring rapid response and root cause analysis.
+ Build strong relationships with business and analytics teams to understand data consumption patterns, prioritize operational needs, and align with business objectives.
+ Drive adoption of best practices for documentation, metadata, lineage, and change management across data operations processes.
+ Mentor and develop a high-performing team of data operations analysts and leads.
**Functional Skills:**
**Must-Have Skills:**
+ Experience managing a team of data engineers in biotech/pharma domain companies.
+ Experience in designing and maintaining data pipelines and analytics solutions that extract, transform, and load data from multiple source systems.
+ Demonstrated hands-on experience with cloud platforms (AWS) and the ability to architect cost-effective and scalable data solutions.
+ Experience managing data workflows in cloud environments such as AWS, Azure, or GCP.
+ Strong problem-solving skills with the ability to analyze complex data flow issues and implement sustainable solutions.
+ Working knowledge of SQL, Python, or scripting languages for process monitoring and automation.
+ Experience collaborating with data engineering, analytics, IT operations, and business teams in a matrixed organization.
+ Familiarity with data governance, metadata management, access control, and regulatory requirements (e.g., GDPR, HIPAA, SOX).
+ Excellent leadership, communication, and stakeholder engagement skills.
+ Well versed with full stack development & DataOps automation, logging frameworks, and pipeline orchestration tools.
+ Strong analytical and problem-solving skills to address complex data challenges.
+ Effective communication and interpersonal skills to collaborate with cross-functional teams.
**Good-to-Have Skills:**
+ Data Engineering Management experience in Biotech/Life Sciences/Pharma
+ Experience using graph databases such as Stardog or Marklogic or Neo4J or Allegrograph, etc.
**Education and Professional Certifications**
+ 9 to 12 years of experience in Computer Science, IT or related field
+ AWS Certified Data Engineer preferred
+ Databricks Certificate preferred
+ Scaled Agile SAFe certification preferred
**Soft Skills:**
+ Excellent analytical and troubleshooting skills
+ Strong verbal and written communication skills
+ Ability to work effectively with global, virtual teams
+ High degree of initiative and self-motivation
+ Ability to manage multiple priorities successfully
+ Team-oriented, with a focus on achieving team goals
+ Strong presentation and public speaking skills
**EQUAL OPPORTUNITY STATEMENT**
Amgen is an Equal Opportunity employer and will consider you without regard to your race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or disability status. We will ensure that individuals with disabilities are provided with reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request an accommodation.
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Data Engineering Manager
Posted 3 days ago
Job Viewed
Job Description
At Amgen, if you feel like you're part of something bigger, it's because you are. Our shared mission-to serve patients living with serious illnesses-drives all that we do.
Since 1980, we've helped pioneer the world of biotech in our fight against the world's toughest diseases. With our focus on four therapeutic areas -Oncology, Inflammation, General Medicine, and Rare Disease- we reach millions of patients each year. As a member of the Amgen team, you'll help make a lasting impact on the lives of patients as we research, manufacture, and deliver innovative medicines to help people live longer, fuller happier lives.
Our award-winning culture is collaborative, innovative, and science based. If you have a passion for challenges and the opportunities that lay within them, you'll thrive as part of the Amgen team. Join us and transform the lives of patients while transforming your career.
**Data Engineering Manager**
**What you will do**
Let's do this. Let's change the world. In this vital role you will lead a team of data engineers to build, optimize, and maintain scalable data architectures, data pipelines, and operational frameworks that support real-time analytics, AI-driven insights, and enterprise-wide data solutions. As a strategic leader, the ideal candidate will drive best practices in data engineering, cloud technologies, and Agile development, ensuring robust governance, data quality, and efficiency. The role requires technical expertise, team leadership, and a deep understanding of cloud data solutions to optimize data-driven decision-making.
+ Lead and mentor a team of data engineers, fostering a culture of innovation, collaboration, and continuous learning for solving complex problems of R&D division.
+ Oversee the development of data extraction, validation, and transformation techniques, ensuring ingested data is of high quality and compatible with downstream systems.
+ Guide the team in writing and validating high-quality code for data ingestion, processing, and transformation, ensuring resiliency and fault tolerance.
+ Drive the development of data tools and frameworks for running and accessing data efficiently across the organization.
+ Oversee the implementation of performance monitoring protocols across data pipelines, ensuring real-time visibility, alerts, and automated recovery mechanisms.
+ Coach engineers in building dashboards and aggregations to monitor pipeline health and detect inefficiencies, ensuring optimal performance and cost-effectiveness.
+ Lead the implementation of self-healing solutions, reducing failure points and improving pipeline stability and efficiency across multiple product features.
+ Oversee data governance strategies, ensuring compliance with security policies, regulations, and data accessibility best practices.
+ Guide engineers in data modeling, metadata management, and access control, ensuring structured data handling across various business use cases.
+ Collaborate with business leaders, product owners, and cross-functional teams to ensure alignment of data architecture with product requirements and business objectives.
+ Prepare team members for key partner discussions by helping assess data costs, access requirements, dependencies, and availability for business scenarios.
+ Drive Agile and Scaled Agile (SAFe) methodologies, handling sprint backlogs, prioritization, and iterative improvements to enhance team velocity and project delivery.
+ Stay up-to-date with emerging data technologies, industry trends, and best practices, ensuring the organization uses the latest innovations in data engineering and architecture.
**What we expect of you**
We are all different, yet we all use our unique contributions to serve patients. We are seeking a seasoned Engineering Manager (Data Engineering) to drive the development and implementation of our data strategy with deep expertise in R&D of Biotech or Pharma domain.
**Basic Qualifications:**
+ Doctorate degree **OR**
+ Master's degree and 4 to 6 years of experience in Computer Science, IT or related field **OR**
+ Bachelor's degree and 6 to 8 years of experience in Computer Science, IT or related field **OR**
+ Diploma and 10 to 12 years of experience in Computer Science, IT or related field
+ Experience leading a team of data engineers in the R&D domain of biotech/pharma companies.
+ Experience architecting and building data and analytics solutions that extract, transform, and load data from multiple source systems.
+ Data Engineering experience in R&D for Biotechnology or pharma industry
+ Demonstrated hands-on experience with cloud platforms (AWS) and the ability to architect cost-effective and scalable data solutions.
+ Proficiency in Python, PySpark, SQL.
+ Experience with dimensional data modeling.
+ Experience working with Apache Spark, Apache Airflow.
+ Experienced with software engineering best-practices, including but not limited to version control (Git, Subversion, etc.), CI/CD (Jenkins, Maven etc.), automated unit testing, and Dev Ops.
+ Experienced with AWS or GCP or Azure cloud services.
+ Understanding of end to end project/product life cycle
+ Well versed with full stack development & DataOps automation, logging frameworks, and pipeline orchestration tools.
+ Strong analytical and problem-solving skills to address complex data challenges.
+ Effective communication and interpersonal skills to collaborate with cross-functional teams.
**Preferred Qualifications:**
+ AWS Certified Data Engineer preferred
+ Databricks Certificate preferred
+ Scaled Agile SAFe certification preferred
+ Project Management certifications preferred
+ Data Engineering Management experience in Biotech/Pharma is a plus
+ Experience using graph databases such as Stardog or Marklogic or Neo4J or Allegrograph, etc.
**Soft Skills:**
+ Excellent analytical and troubleshooting skills
+ Strong verbal and written communication skills
+ Ability to work effectively with global, virtual teams
+ High degree of initiative and self-motivation
+ Ability to handle multiple priorities successfully
+ Team-oriented, with a focus on achieving team goals
+ Strong presentation and public speaking skills
**What you can expect of us**
As we work to develop treatments that take care of others, we also work to care for your professional and personal growth and well-being. From our competitive benefits to our collaborative culture, we'll support your journey every step of the way.
In addition to the base salary, Amgen offers competitive and comprehensive Total Rewards Plans that are aligned with local industry standards.
**Apply now and make a lasting impact with the Amgen team.**
**careers.amgen.com**
As an organization dedicated to improving the quality of life for people around the world, Amgen fosters an inclusive environment of diverse, ethical, committed and highly accomplished people who respect each other and live the Amgen values to continue advancing science to serve patients. Together, we compete in the fight against serious disease.
Amgen is an Equal Opportunity employer and will consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability status, or any other basis protected by applicable law.
We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.
Data Engineering Manager
Posted 2 days ago
Job Viewed
Job Description
The Data & Insights organization at Insight Global delivers Trusted Data & Verified Insights to drive strategic decision-making across the company. As the first Data Engineering Manager based in Hyderabad, India, you will play a foundational role in establishing and growing a high-performing offshore team. You will lead efforts to build and maintain the core data estate that powers Business Intelligence, Data Science, and Machine Learning use cases, while also overseeing platform operations and reliability.
Key Responsibilities
· Serve as the founding Data Engineering Manager in Hyderabad, responsible for building and scaling the offshore team.
· Lead and mentor a growing team of Data Engineers, fostering a culture of innovation, accountability, and continuous improvement.
· Oversee both development and operations of the data platform, including monitoring, bug fixing, and SLA adherence.
· Drive Agile/Scrum best practices, conduct regular 1:1s, team meetings, and performance reviews to support career development.
· Define team growth strategy, manage capacity planning, and participate in hiring and onboarding.
· Collaborate with cross-functional partners in Product Strategy, Delivery, QA, Architecture, SRE, and Program Management.
· Ensure data security and governance in partnership with Information Security and Data Governance teams.
· Champion Insight Global’s culture and shared values
Technical Focus
· Lead team responsible for initiatives to retire SQL Server data pipelines and implement a modern Databricks Medallion Lakehouse architecture
· Promote best practices in CI/CD, automated testing, and metadata management.
· Support batch and streaming data environments, ensuring high performance and reliability, and data quality.
· Own operational dashboards, pipeline health monitoring, and incident response processes.
Qualifications
· Bachelor’s degree in a technical field.
· 10+ years of experience in data engineering, analytics, or data science.
· 5+ years of experience managing data engineering teams.
· Strong expertise in SQL, Python (PySpark), Databricks, and Azure Data Factory.
· Proven ability to structure data for analytics and machine learning.
· Excellent communication and collaboration skills across business and technical teams.
· Experience with Unity Catalog and data governance frameworks is preferred.
Data Engineering Manager
Posted today
Job Viewed
Job Description
Data Engineering Manager - Azure & Python
Experience: Years Exp.
Salary: Competitive
Preferred Notice Period: 30 Days
Shift: 10:00 AM to 7:00 PM IST
Opportunity Type: Noida (Remote for 6 months, Later Hybrid)
Placement Type: Permanent
(*Note: This is a requirement for one of Uplers' Clients)
Must have skills required :
Engineering management, Data Engineering, Azure Data Factory, Python, SQL OR NoSQL OR Azure, Backend OR FullStack
Nuaav (One of Uplers' Clients) is Looking for:
An Engineering Manager who is passionate about their work, eager to learn and grow, and who is committed to delivering exceptional results. If you are a team player, with a positive attitude and a desire to make a difference, then we want to hear from you.
Role Overview Description
As Engineering Manager Data Engineering at Nuaav, you will lead a talented team of data engineers focused on architecting and delivering enterprise-grade, scalable data platforms on Microsoft Azure. This role demands deep expertise in Azure cloud services and Python programming, combined with strong leadership skills to drive technical strategy, team growth, and execution of robust data infrastructures.
Key Responsibilities
- Lead, mentor, and grow a high-performing data engineering team delivering next-generation data solutions on Azure.
- Architect and oversee the development of scalable data pipelines and analytics platforms using Azure Data Lake, Data Factory, Databricks, and Synapse.
- Drive technical execution of data warehousing and BI solutions with advanced Python programming (including PySpark).
- Enforce high standards for data quality, consistency, governance, and security across data systems.
- Collaborate cross-functionally with product managers, software engineers, data scientists, and analysts to enable business insights and ML initiatives.
- Define and implement best practices for ETL design, data integration, and cloud-native workflows.
- Continuously optimize data processing for performance, reliability, and cost efficiency.
- Oversee technical documentation, onboarding, and process compliance within the engineering team.
- Stay abreast of industry trends in data engineering, Azure technologies, and cloud security to maintain cutting-edge capabilities.
Qualifications
- Bachelors or Masters degree in Computer Science, Engineering, or related field.
- 5+ years data engineering experience with significant team leadership or management exposure.
- Strong expertise in designing and building cloud data solutions on Microsoft Azure (Data Lake, Synapse, Data Factory, Databricks).
- Advanced Python skills for data transformation, automation, and pipeline development (including PySpark).
- Solid SQL skills; experience with big data tools like Spark, Hive, or Scala is a plus.
- Knowledge of CI/CD pipelines, DevOps practices, and Infrastructure-as-Code (Terraform, GitHub Actions).
- Experience with data security, governance, and compliance frameworks in cloud environments.
- Excellent communication, leadership, and project management capabilities.
Desired Skills
- Azure Data Factory, Databricks, Synapse Analytics expert.
- Proficiency with Python, PySpark, SQL for ETL and data workflows.
- Familiarity with big data frameworks (Spark, HDFS).
- Hands-on experience with DevOps tools and container technologies (GitHub, Docker, Kubernetes).
- Strong cross-functional collaboration and team mentoring skills.
This role offers an exciting opportunity to lead and scale mission-critical data infrastructure at Nuaav, a firm known for its boutique approach combining technical mastery with personalized client impact and agility in delivery. Candidates will thrive in a fast-paced, innovative setting with a clear path for growth and influence.
Why Join Nuaav?
- Opportunity to work in a strong AI driven consulting firm with direct client engagement and high-impact projects.
- Be part of a dynamic environment focused on innovation, agility, and quality over volume.
- Exposure to cutting-edge technologies across data engineering, AI, and product platforms.
- Work on global-scale digital transformation projects with close collaboration alongside senior consultants and corporate leaders.
- A culture that values personalized growth, client-centric excellence, and thought leadership.
How to apply for this opportunity:
Easy 3-Step Process:
1. Click On Apply And Register or log in on our portal
Upload updated Resume & Complete the Screening Form
Increase your chances to get shortlisted & meet the client for the Interview
About Our Client:
Nuaav is a boutique technology consulting firm focused on delivering innovative, scalable, and secure data engineering and AI solutions.
About Uplers:
Our goal is to make hiring and getting hired reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant product and engineering job opportunities and progress in their career.
(Note: There are many more opportunities apart from this on the portal.)
So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you