1,351 Data Engineering Manager jobs in India

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start **Caring. Connecting. Growing together.**
We are looking for a skilled Data Engineer to design, build, and maintain scalable, secure, and high-performance data solutions. This role spans the full data engineering lifecycle - from research and architecture to deployment and support- within cloud-native environments, with a strong focus on AWS and Kubernetes (EKS).
**Primary Responsibilities:**
+ **Data Engineering Lifecycle:** Lead research, proof of concept, architecture, development, testing, deployment, and ongoing maintenance of data solutions
+ **Data Solutions:** Design and implement modular, flexible, secure, and reliable data systems that scale with business needs
+ **Instrumentation and Monitoring:** Integrate pipeline observability to detect and resolve issues proactively
+ **Troubleshooting and Optimization:** Develop tools and processes to debug, optimize, and maintain production systems
+ **Tech Debt Reduction:** Identify and address legacy inefficiencies to improve performance and maintainability
+ **Debugging and Troubleshooting:** Quickly diagnose and resolve unknown issues across complex systems
+ **Documentation and Governance:** Maintain clear documentation of data models, transformations, and pipelines to ensure security and governance compliance
+ **Cloud Expertise:** Leverage advanced skills in AWS and EKS to build, deploy, and scale cloud-native data platforms
+ **Cross-Functional Support:** Collaborate with analytics, application development, and business teams to enable data-driven solutions
+ **Team Leadership:** Lead and mentor engineering teams to ensure operational efficiency and innovation
+ Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so
**Required Qualifications:**
+ Bachelor's degree in Computer Science or related field
+ 5+ years of experience in data engineering or related roles
+ Proven experience designing and deploying scalable, secure, high-quality data solutions
+ Solid expertise in full Data Engineering lifecycle (research to maintenance)
+ Advanced AWS and EKS knowledge
+ Proficient in CI/CD, IaC, and addressing tech debt
+ Proven skilled in monitoring and instrumentation of data pipelines
+ Proven advanced troubleshooting and performance optimization abilities
+ Proven ownership mindset with ability to manage multiple components
+ Proven effective cross-functional collaborator (DS, SMEs, and external teams).
+ Proven exceptional debugging and problem-solving skills
+ Proven solid individual contributor with a team-first approach
_At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age, location and income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission._
_#njp_

**ABOUT AMGEN**
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**
+ Any Degree and 9-13 years of experience
+ 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.

**ABOUT AMGEN**
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.

**ABOUT AMGEN**
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.

**ABOUT AMGEN**
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.

Join Amgen's Mission of Serving Patients
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.

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together.

We are looking for a skilled Data Engineer to design, build, and maintain scalable, secure, and high-performance data solutions. This role spans the full data engineering lifecycle - from research and architecture to deployment and support- within cloud-native environments, with a strong focus on AWS and Kubernetes (EKS). 

Primary Responsibilities:

Data Engineering Lifecycle: Lead research, proof of concept, architecture, development, testing, deployment, and ongoing maintenance of data solutions

Data Solutions: Design and implement modular, flexible, secure, and reliable data systems that scale with business needs

Instrumentation and Monitoring: Integrate pipeline observability to detect and resolve issues proactively

Troubleshooting and Optimization: Develop tools and processes to debug, optimize, and maintain production systems

Tech Debt Reduction: Identify and address legacy inefficiencies to improve performance and maintainability

Debugging and Troubleshooting: Quickly diagnose and resolve unknown issues across complex systems

Documentation and Governance: Maintain clear documentation of data models, transformations, and pipelines to ensure security and governance compliance

Cloud Expertise: Leverage advanced skills in AWS and EKS to build, deploy, and scale cloud-native data platforms

Cross-Functional Support: Collaborate with analytics, application development, and business teams to enable data-driven solutions 

Team Leadership: Lead and mentor engineering teams to ensure operational efficiency and innovation

Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so

Required Qualifications:

Bachelor’s degree in Computer Science or related field

5+ years of experience in data engineering or related roles

Proven experience designing and deploying scalable, secure, high-quality data solutions

Solid expertise in full Data Engineering lifecycle (research to maintenance)

Advanced AWS and EKS knowledge

Proficient in CI/CD, IaC, and addressing tech debt

Proven skilled in monitoring and instrumentation of data pipelines

Proven advanced troubleshooting and performance optimization abilities

Proven ownership mindset with ability to manage multiple components

Proven effective cross-functional collaborator (DS, SMEs, and external teams).

Proven exceptional debugging and problem-solving skills

Proven solid individual contributor with a team-first approach

At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone–of every race, gender, sexuality, age, location and income–deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes — an enterprise priority reflected in our mission.

#njp

Job Title:  Data Engineering  Location: Udaipur / Jaipur  Experience Required: 10 to 12 years 

About Us  

Kadel Labs is a deep-tech IT services company dedicated to transforming businesses with cutting-edge solutions. Our expertise spans Data Analytics, Engineering, and Visualization; Cloud services including DevOps, InfoSecOps, and InfraOps; Software development and modernization; and Generative AI-driven business applications. As a trusted partner of DataBricks, Azure, AWS, WebMethods, and Bitrix24 CRM, we empower businesses with innovative, reliable, and scalable technology solutions. 

About Role:

We are seeking an experienced and driven Engineering Manager – Data Engineering to lead the delivery of end-to-end data platform solutions for our clients. This role involves managing a team of data engineers and overseeing projects that span cloud data platforms, ELT pipelines, and business intelligence tools.

You’ll play a critical role in ensuring successful project execution, client satisfaction, and continuous team development while working with leading technologies such as Databricks, Azure Synapse, Microsoft Fabric, Snowflake, Power BI, Tableau, and more.

This is a hybrid role requiring technical depth, leadership skills, and client-facing experience.

Key Responsibilities

Lead and mentor a team of data engineers delivering projects across multiple client engagements.Own the end-to-end delivery of cloud-based data solutions, from ingestion to modeling to visualization.Architect and guide the implementation of data platforms using tools like Databricks, Synapse, Fabric, and Snowflake .Oversee the development of scalable, reliable data pipelines and warehouse structures.Collaborate with internal and client-side project managers, analysts, and stakeholders to align technical solutions with business goals.Ensure delivery best practices: CI/CD, version control, peer reviews, testing, monitoring, and documentation.Support pre-sales by providing solution designs, estimates, and technical guidance for proposals.Allocate resources effectively across projects and track performance metrics, timelines, and deliverables.Foster a culture of technical excellence, continuous improvement, and learning within the team.

Skills Required:

12+ years in data engineering or related fields, with at least 3–4 years managing engineering teams in a consulting or service company environment.Proven experience delivering data platform solutions for enterprise clients.Hands-on expertise in at least two of the following:DatabricksAzure Synapse AnalyticsMicrosoft FabricSnowflakeStrong understanding of ELT/ETL patterns, data modeling (dimensional & data vault), and cloud storage (e.g., ADLS, S3).Solid programming and scripting experience (SQL, Python, or Scala).Familiarity with BI/visualization tools: Power BI, Tableau, Sigma, Qlik, Google LookerExperience working in cloud environments: Azure, AWS, or GCP.Excellent communication and client-facing skills.

Nice to Have

Experience in data governance, security, and compliance (e.g., GDPR, HIPAA).Familiarity with orchestration and automation tools like Azure Data Factory, dbt, or Apache Airflow.Exposure to Agile delivery, project estimation, and team scaling.Experience mentoring junior engineers and building high-performance teams.