12,716 Engineering Team jobs in India
Engineering Associate - Engineering
Posted 3 days ago
Job Viewed
Job Description
**Job Number** 25126692
**Job Category** Engineering & Facilities
**Location** Le Meridien Hyderabad, Plot No 132 Miyapur Road, Hyderabad, Telangana, India, 500032VIEW ON MAP ( Full Time
**Located Remotely?** N
**Position Type** Non-Management
**POSITION SUMMARY**
Respond and attend to guest repair requests. Communicate with guests/customers to resolve maintenance issues. Perform preventive maintenance on tools and kitchen and mechanical room equipment, including cleaning and lubrication. Visually inspect tools, equipment, or machines. Carry equipment (e.g., tools, radio). Identify, locate, and operate all shut-off valves for equipment and all utility shut-offs for buildings. Maintain maintenance inventory and requisition parts and supplies as needed. Communicate each day's activities and problems that occur to the other shifts using approved communication programs and standards. Display basic knowledge or ability to acquire knowledge in the following categories: air conditioning and refrigeration, electrical, mechanical, plumbing, pneumatic/electronic systems and controls, carpentry and finish skills, kitchen equipment, vehicles, energy conservation, and/or general building. Perform all surface preparation, painting, minor drywall and wood trim repair, light bulb and A/C filter replacement and the complete and thorough cleanup of the painting or repair area. Test, troubleshoot and perform basic repair on all types of equipment, plumbing (e.g., plunge toilets and unclog drains), electrical components including lamps, cosmetic items, extension cords, vacuum cleaners, internet devices, replace electrical switches and outlets, and other guestroom items. Program TV's and perform general housekeeping and engineering-related inventory duties. Use the Lockout/Tagout system before performing any maintenance work. Perform repairs on interior and exterior landscaping as well as external landscaping sprinklers. Display basic computer skills including inputting air handler schedules and making temperature changes.
Follow all company and safety and security policies and procedures; report any maintenance problems, safety hazards, accidents, or injuries; complete safety training and certifications; and properly store flammable materials. Ensure uniform and personal appearance are clean and professional, maintain confidentiality of proprietary information, and protect company assets. Welcome and acknowledge all guests according to company standards, anticipate and address guests' service needs, assist individuals with disabilities, and thank guests with genuine appreciation. Adhere to quality expectations and standards. Develop and maintain positive working relationships with others, support team to reach common goals, and listen and respond appropriately to the concerns of other employees. Speak with others using clear and professional language. Move, lift, carry, push, pull, and place objects weighing less than or equal to 50 pounds without assistance and heavier lifting or movement tasks with assistance. Move up and down stairs, service ramps, and/or ladders. Reach overhead and below the knees, including bending, twisting, pulling, and stooping. Enter and locate work-related information using computers. Perform other reasonable job duties as requested.
PREFERRED QUALIFICATIONS
Education: High school diploma or G.E.D equivalent.
Related Work Experience: Some experience in general maintenance, exterior and interior surface preparation and painting.
Experience in hotel engineering or maintenance a plus.
Supervisory Experience: No supervisory experience.
REQUIRED QUALIFICATIONS
License or Certification: Driver's License
_At Marriott International, we are dedicated to being an equal opportunity employer, welcoming all and providing access to opportunity. We actively foster an environment where the unique backgrounds of our associates are valued and celebrated. Our greatest strength lies in the rich blend of culture, talent, and experiences of our associates. We are committed to non-discrimination on any protected basis, including disability, veteran status, or other basis protected by applicable law._
At Le Méridien, we are inspired by the era of glamorous travel, celebrating each culture through the distinctly European spirit of savouring the good life. Our guests are curious and creative, cosmopolitan culture seekers that appreciate moments of connection and slowing down to savour the destination. We provide authentic, chic and memorable service along with experiences that inspire guests to savour the good life. We're looking for curious and creative people to join our team. If you appreciate connecting with like-minded guests and have a deep desire to create memorable experiences, we invite you to explore career opportunities with Le Méridien. In joining Le Méridien, you join a portfolio of brands with Marriott International. **Be** where you can do your best work, **begin** your purpose, **belong** to an amazing global team, and **become** the best version of you.
Engineering Manager, HR Engineering
Posted 1 day ago
Job Viewed
Job Description
+ Bachelor's degree in Computer Science, Engineering, or a related field or equivalent practical experience.
+ 8 years of experience in managing and leading software engineering teams with AI/ML.
**Preferred qualifications:**
+ 7 years of experience in software development with AI/ML applications.
+ Experience in the development and deployment of AI/ML systems with HR data.
Like Google's own ambitions, the work of a Software Engineer goes beyond just Search. Software Engineering Managers have not only the technical expertise to take on and provide technical leadership to major projects, but also manage a team of Engineers. You not only optimize your own code but make sure Engineers are able to optimize theirs. As a Software Engineering Manager you manage your project goals, contribute to product strategy and help develop your team. Teams work all across the company, in areas such as information retrieval, artificial intelligence, natural language processing, distributed computing, large-scale system design, networking, security, data compression, user interface design; the list goes on and is growing every day. Operating with scale and speed, our exceptional software engineers are just getting started -- and as a manager, you guide the way.
With technical and leadership expertise, you manage engineers across multiple teams and locations, a large product budget and oversee the deployment of large-scale projects across multiple sites internationally.
The Human Resources Engineering (HRE) team at Google is dedicated to building technology solutions that empower Google's global workforce. We leverage the power of data and AI/ML to optimize Human Resources (HR) processes, enhance employee experiences, and drive organizational efficiency.
In this role, you will be applying Artificial Intelligence (AI) to solve tests within a fluid domain.
At Corp Eng, we build world-leading business solutions that scale a more helpful Google for everyone. As Google's IT organization, we provide end-to-end solutions for organizations across Google. We deliver the right tools, platforms, and experiences for all Googlers as they create more helpful products and services for everyone. In the simplest terms, we are Google for Googlers.
**Responsibilities:**
+ Provide technical leadership and direction for a significant portion of the AI Software Engineering organization aligning with HRE and Artificial Intelligence/Machine Learning (AI/ML) strategies.
+ Manage and mentor a team of Engineering Managers (EMs) or lead teams of AI Software Engineers, promoting a collaborative environment.
+ Drive the technical strategy for major AI/ML initiatives within HRE, ensuring scalability, reliability, security, and maintainability of our systems.
+ Collaborate with executive product leaders and HR stakeholders to define product roadmaps, influence direction, and translate business objectives into AI/ML solutions.
+ Oversee the design, development, and deployment of AI/ML systems and infrastructure related to HR applications (e.g., talent acquisition, performance management, employee experience, workforce planning, compensation and benefits).
Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also and If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form:
Engineering Manager - Data Engineering
Posted 1 day ago
Job Viewed
Job Description
About Licious:
Licious is India’s leading D2C fresh meat and seafood brand, revolutionizing the way meat is sourced, processed, and delivered. We’re a technology-first company obsessed with ensuring the highest standards in food quality, cold chain logistics, and customer delight.
---
Role Overview:
We are looking for a seasoned Data Platform & DevOps Engineering Manager to lead the development and operations of our modern, cloud-native data and infrastructure platform. You’ll drive the architecture and execution of large-scale data processing, analytics systems, and DevOps practices that enable high-quality insights and rapid product iteration.
This is a strategic and hands-on leadership role, managing a team of data engineers, DevOps specialists, and cloud platform engineers.
---
Key Responsibilities:
Data Platform & Engineering:
Architect, build, and maintain scalable and secure data infrastructure using tools like Apache Hadoop, Hive, Spark, Kafka, Airflow, and Delta Lake.
Develop robust ETL/ELT pipelines, data models, and streaming data workflows to support analytics, business intelligence, and machine learning use cases.
Optimize data storage and compute using cloud-native solutions (AWS S3, Redshift, EMR, Glue, Athena, etc.).
Integrate with modern data stack tools such as dbt, Snowflake, BigQuery, and Fivetran (or custom connectors).
Ensure data quality, lineage, cataloging, and observability using tools like Apache Atlas, Great Expectations, and Amundsen.
Collaborate closely with Product, Engineering, and Data Science teams to deliver accurate, timely, and actionable data.
ML & Advanced Analytics Enablement:
Support Data Science and AI/ML teams by maintaining model pipelines and training infrastructure.
Enable MLOps frameworks using MLflow, SageMaker, PyTorch, or TensorFlow for seamless experimentation and deployment.
Manage model versioning, metadata tracking, and real-time inference workflows.
DevOps & Platform Engineering:
Lead the design and implementation of robust CI/CD pipelines, version control, testing, and deployment practices.
Implement Infrastructure as Code (IaC) using Terraform, Ansible, or Pulumi.
Manage containerization and orchestration platforms like Docker, Kubernetes (EKS preferred).
Own cloud infrastructure (preferably AWS), including networking, security, cost governance, and compliance.
Set up monitoring and alerting using Prometheus, Grafana, ELK Stack, or DataDog.
Leadership & People Management:
Hire, coach, and mentor a team of 8–12 data, devops and platform engineers
Set clear objectives, track performance, and build a culture of ownership, continuous learning, and innovation.
Collaborate cross-functionally to translate business needs into scalable engineering solutions.
—
Required Skills & Qualifications:
-Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
-10+ years of experience in data engineering, DevOps, or infrastructure roles, with at least 3 years in a technical leadership or managerial capacity.
-Strong experience with cloud platforms (AWS preferred), distributed data systems, and large-scale batch + real-time data processing.
-Hands-on proficiency with tools like Kafka, Airflow, Hadoop, Hive, Spark, dbt, PyTorch, MLflow, and Docker/Kubernetes.
-Proven experience in building and maintaining enterprise data platforms and ML Ops pipelines.
-Strong understanding of CI/CD, GitOps, system monitoring, SRE, and cost optimization best practices.
-Exceptional problem-solving skills, stakeholder communication, and team leadership.
-Ensure platform security, data protection compliance, and cloud infra governance
• Incident Management / SRE Practices
-Own platform reliability, incident management processes, incident retros, and on-call practices
• Infra Scale & Optimization Responsibilities:
-Plan for infra scaling and performance benchmarking to support growing order volumes and data ingestion rates
-Operational KPIs/OKRs will include - Own infra uptime , pipeline latency , model deployment TAT , cloud cost optimization & Elevate Security & Privacy Management
---
Nice to Have:
Experience with data privacy regulations (GDPR, SOC2, etc.)
Exposure to security best practices in DevOps and cloud infra.
Familiarity with Data Mesh or Lakehouse architecture.
Engineering Manager - Data Engineering
Posted today
Job Viewed
Job Description
About Licious:
Licious is India’s leading D2C fresh meat and seafood brand, revolutionizing the way meat is sourced, processed, and delivered. We’re a technology-first company obsessed with ensuring the highest standards in food quality, cold chain logistics, and customer delight.
---
Role Overview:
We are looking for a seasoned Data Platform & DevOps Engineering Manager to lead the development and operations of our modern, cloud-native data and infrastructure platform. You’ll drive the architecture and execution of large-scale data processing, analytics systems, and DevOps practices that enable high-quality insights and rapid product iteration.
This is a strategic and hands-on leadership role, managing a team of data engineers, DevOps specialists, and cloud platform engineers.
---
Key Responsibilities:
Data Platform & Engineering:
Architect, build, and maintain scalable and secure data infrastructure using tools like Apache Hadoop, Hive, Spark, Kafka, Airflow, and Delta Lake.
Develop robust ETL/ELT pipelines, data models, and streaming data workflows to support analytics, business intelligence, and machine learning use cases.
Optimize data storage and compute using cloud-native solutions (AWS S3, Redshift, EMR, Glue, Athena, etc.).
Integrate with modern data stack tools such as dbt, Snowflake, BigQuery, and Fivetran (or custom connectors).
Ensure data quality, lineage, cataloging, and observability using tools like Apache Atlas, Great Expectations, and Amundsen.
Collaborate closely with Product, Engineering, and Data Science teams to deliver accurate, timely, and actionable data.
ML & Advanced Analytics Enablement:
Support Data Science and AI/ML teams by maintaining model pipelines and training infrastructure.
Enable MLOps frameworks using MLflow, SageMaker, PyTorch, or TensorFlow for seamless experimentation and deployment.
Manage model versioning, metadata tracking, and real-time inference workflows.
DevOps & Platform Engineering:
Lead the design and implementation of robust CI/CD pipelines, version control, testing, and deployment practices.
Implement Infrastructure as Code (IaC) using Terraform, Ansible, or Pulumi.
Manage containerization and orchestration platforms like Docker, Kubernetes (EKS preferred).
Own cloud infrastructure (preferably AWS), including networking, security, cost governance, and compliance.
Set up monitoring and alerting using Prometheus, Grafana, ELK Stack, or DataDog.
Leadership & People Management:
Hire, coach, and mentor a team of 8–12 data, devops and platform engineers
Set clear objectives, track performance, and build a culture of ownership, continuous learning, and innovation.
Collaborate cross-functionally to translate business needs into scalable engineering solutions.
—
Required Skills & Qualifications:
-Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
-10+ years of experience in data engineering, DevOps, or infrastructure roles, with at least 3 years in a technical leadership or managerial capacity.
-Strong experience with cloud platforms (AWS preferred), distributed data systems, and large-scale batch + real-time data processing.
-Hands-on proficiency with tools like Kafka, Airflow, Hadoop, Hive, Spark, dbt, PyTorch, MLflow, and Docker/Kubernetes.
-Proven experience in building and maintaining enterprise data platforms and ML Ops pipelines.
-Strong understanding of CI/CD, GitOps, system monitoring, SRE, and cost optimization best practices.
-Exceptional problem-solving skills, stakeholder communication, and team leadership.
-Ensure platform security, data protection compliance, and cloud infra governance
• Incident Management / SRE Practices
-Own platform reliability, incident management processes, incident retros, and on-call practices
• Infra Scale & Optimization Responsibilities:
-Plan for infra scaling and performance benchmarking to support growing order volumes and data ingestion rates
-Operational KPIs/OKRs will include - Own infra uptime , pipeline latency , model deployment TAT , cloud cost optimization & Elevate Security & Privacy Management
---
Nice to Have:
Experience with data privacy regulations (GDPR, SOC2, etc.)
Exposure to security best practices in DevOps and cloud infra.
Familiarity with Data Mesh or Lakehouse architecture.
Engineering Manager - Data Engineering
Posted 1 day ago
Job Viewed
Job Description
Licious is India’s leading D2C fresh meat and seafood brand, revolutionizing the way meat is sourced, processed, and delivered. We’re a technology-first company obsessed with ensuring the highest standards in food quality, cold chain logistics, and customer delight.
---
Role Overview:
We are looking for a seasoned Data Platform & DevOps Engineering Manager to lead the development and operations of our modern, cloud-native data and infrastructure platform. You’ll drive the architecture and execution of large-scale data processing, analytics systems, and DevOps practices that enable high-quality insights and rapid product iteration.
This is a strategic and hands-on leadership role, managing a team of data engineers, DevOps specialists, and cloud platform engineers.
---
Key Responsibilities:
Data Platform & Engineering:
Architect, build, and maintain scalable and secure data infrastructure using tools like Apache Hadoop, Hive, Spark, Kafka, Airflow, and Delta Lake.
Develop robust ETL/ELT pipelines, data models, and streaming data workflows to support analytics, business intelligence, and machine learning use cases.
Optimize data storage and compute using cloud-native solutions (AWS S3, Redshift, EMR, Glue, Athena, etc.).
Integrate with modern data stack tools such as dbt, Snowflake, BigQuery, and Fivetran (or custom connectors).
Ensure data quality, lineage, cataloging, and observability using tools like Apache Atlas, Great Expectations, and Amundsen.
Collaborate closely with Product, Engineering, and Data Science teams to deliver accurate, timely, and actionable data.
ML & Advanced Analytics Enablement:
Support Data Science and AI/ML teams by maintaining model pipelines and training infrastructure.
Enable MLOps frameworks using MLflow, SageMaker, PyTorch, or TensorFlow for seamless experimentation and deployment.
Manage model versioning, metadata tracking, and real-time inference workflows.
DevOps & Platform Engineering:
Lead the design and implementation of robust CI/CD pipelines, version control, testing, and deployment practices.
Implement Infrastructure as Code (IaC) using Terraform, Ansible, or Pulumi.
Manage containerization and orchestration platforms like Docker, Kubernetes (EKS preferred).
Own cloud infrastructure (preferably AWS), including networking, security, cost governance, and compliance.
Set up monitoring and alerting using Prometheus, Grafana, ELK Stack, or DataDog.
Leadership & People Management:
Hire, coach, and mentor a team of 8–12 data, devops and platform engineers
Set clear objectives, track performance, and build a culture of ownership, continuous learning, and innovation.
Collaborate cross-functionally to translate business needs into scalable engineering solutions.
—
Required Skills & Qualifications:
-Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
-10+ years of experience in data engineering, DevOps, or infrastructure roles, with at least 3 years in a technical leadership or managerial capacity.
-Strong experience with cloud platforms (AWS preferred), distributed data systems, and large-scale batch + real-time data processing.
-Hands-on proficiency with tools like Kafka, Airflow, Hadoop, Hive, Spark, dbt, PyTorch, MLflow, and Docker/Kubernetes.
-Proven experience in building and maintaining enterprise data platforms and ML Ops pipelines.
-Strong understanding of CI/CD, GitOps, system monitoring, SRE, and cost optimization best practices.
-Exceptional problem-solving skills, stakeholder communication, and team leadership.
-Ensure platform security, data protection compliance, and cloud infra governance
• Incident Management / SRE Practices
-Own platform reliability, incident management processes, incident retros, and on-call practices
• Infra Scale & Optimization Responsibilities:
-Plan for infra scaling and performance benchmarking to support growing order volumes and data ingestion rates
-Operational KPIs/OKRs will include - Own infra uptime , pipeline latency , model deployment TAT , cloud cost optimization & Elevate Security & Privacy Management
---
Nice to Have:
Experience with data privacy regulations (GDPR, SOC2, etc.)
Exposure to security best practices in DevOps and cloud infra.
Familiarity with Data Mesh or Lakehouse architecture.
Engineering Manager - Data Engineering
Posted today
Job Viewed
Job Description
About Licious:
Licious is India’s leading D2C fresh meat and seafood brand, revolutionizing the way meat is sourced, processed, and delivered. We’re a technology-first company obsessed with ensuring the highest standards in food quality, cold chain logistics, and customer delight.
---
Role Overview:
We are looking for a seasoned Data Platform & DevOps Engineering Manager to lead the development and operations of our modern, cloud-native data and infrastructure platform. You’ll drive the architecture and execution of large-scale data processing, analytics systems, and DevOps practices that enable high-quality insights and rapid product iteration.
This is a strategic and hands-on leadership role, managing a team of data engineers, DevOps specialists, and cloud platform engineers.
---
Key Responsibilities:
Data Platform & Engineering:
Architect, build, and maintain scalable and secure data infrastructure using tools like Apache Hadoop, Hive, Spark, Kafka, Airflow, and Delta Lake.
Develop robust ETL/ELT pipelines, data models, and streaming data workflows to support analytics, business intelligence, and machine learning use cases.
Optimize data storage and compute using cloud-native solutions (AWS S3, Redshift, EMR, Glue, Athena, etc.).
Integrate with modern data stack tools such as dbt, Snowflake, BigQuery, and Fivetran (or custom connectors).
Ensure data quality, lineage, cataloging, and observability using tools like Apache Atlas, Great Expectations, and Amundsen.
Collaborate closely with Product, Engineering, and Data Science teams to deliver accurate, timely, and actionable data.
ML & Advanced Analytics Enablement:
Support Data Science and AI/ML teams by maintaining model pipelines and training infrastructure.
Enable MLOps frameworks using MLflow, SageMaker, PyTorch, or TensorFlow for seamless experimentation and deployment.
Manage model versioning, metadata tracking, and real-time inference workflows.
DevOps & Platform Engineering:
Lead the design and implementation of robust CI/CD pipelines, version control, testing, and deployment practices.
Implement Infrastructure as Code (IaC) using Terraform, Ansible, or Pulumi.
Manage containerization and orchestration platforms like Docker, Kubernetes (EKS preferred).
Own cloud infrastructure (preferably AWS), including networking, security, cost governance, and compliance.
Set up monitoring and alerting using Prometheus, Grafana, ELK Stack, or DataDog.
Leadership & People Management:
Hire, coach, and mentor a team of 8–12 data, devops and platform engineers
Set clear objectives, track performance, and build a culture of ownership, continuous learning, and innovation.
Collaborate cross-functionally to translate business needs into scalable engineering solutions.
—
Required Skills & Qualifications:
-Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
-10+ years of experience in data engineering, DevOps, or infrastructure roles, with at least 3 years in a technical leadership or managerial capacity.
-Strong experience with cloud platforms (AWS preferred), distributed data systems, and large-scale batch + real-time data processing.
-Hands-on proficiency with tools like Kafka, Airflow, Hadoop, Hive, Spark, dbt, PyTorch, MLflow, and Docker/Kubernetes.
-Proven experience in building and maintaining enterprise data platforms and ML Ops pipelines.
-Strong understanding of CI/CD, GitOps, system monitoring, SRE, and cost optimization best practices.
-Exceptional problem-solving skills, stakeholder communication, and team leadership.
-Ensure platform security, data protection compliance, and cloud infra governance
• Incident Management / SRE Practices
-Own platform reliability, incident management processes, incident retros, and on-call practices
• Infra Scale & Optimization Responsibilities:
-Plan for infra scaling and performance benchmarking to support growing order volumes and data ingestion rates
-Operational KPIs/OKRs will include - Own infra uptime , pipeline latency , model deployment TAT , cloud cost optimization & Elevate Security & Privacy Management
---
Nice to Have:
Experience with data privacy regulations (GDPR, SOC2, etc.)
Exposure to security best practices in DevOps and cloud infra.
Familiarity with Data Mesh or Lakehouse architecture.
Engineering Manager, Solutions Engineering
Posted today
Job Viewed
Job Description
Who we are
About Stripe
Stripe is a financial infrastructure platform for businesses. Millions of companies - from the world’s largest enterprises to the most ambitious startups - use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career.
About the team
The Solutions Engineering team’s mission is to unlock Productivity across all of Stripe’s Internal Systems. We build Solutions to transform core processes for Finance, Accounting, People, Legal, Sales, Marketing and more. We orchestrate the full automation lifecycle: using AI for planning, analysis and reasoning and deterministic scripts + code + pipelines for reliable & trustworthy execution. We enable tech and non-tech to build hybrid Code + NoCode automations while working with central Operations, Developer Productivity, Infra and ML teams on behalf of all Internal Systems customers to build powerful platforms together.
What you’ll do
We’re looking for an experienced Engineering Manager with a passion for streamlining complex systems and driving operational efficiency. In this role, you'll analyze existing processes across Stripe’s internal systems, leverage automation platforms where possible, and design new solutions when needed. You will implement cutting-edge automation solutions including AI Agents, Robotic Process Automation (RPA), data pipelines, and by building best-in-class platforms. You’ll be responsible for continuously improving workflows to maximize efficiency and deliver meaningful business impact across a broad set of internal stakeholders.
Responsibilities
Who you are
We're looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.
Minimum requirements
Preferred qualifications
In-office expectations
Office-assigned Stripes in most of our locations are currently expected to spend at least 50% of the time in a given month in their local office or with users. This expectation may vary depending on role, team and location. For example, Stripes in Stripe Delivery Center roles in Mexico City, Mexico and Bengaluru, India work 100% from the office. Also, some teams have greater in-office attendance requirements, to appropriately support our users and workflows, which the hiring manager will discuss. This approach helps strike a balance between bringing people together for in-person collaboration and learning from each other, while supporting flexibility when possible.Pay and benefits
Stripe does not yet include pay ranges in job postings in every country. Stripe strongly values pay transparency and is working toward pay transparency globally.
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Engineering Manager- Platform Engineering
Posted today
Job Viewed
Job Description
- Lead design, development, and scalability of high-throughput, low-latency distributed systems.
- Manage and mentor engineering teams while driving technical excellence and team growth.
- Collaborate cross-functionally with product and design teams to deliver innovative solutions.
- Drive execution and ensure quality through regular reviews, feedback loops, and system monitoring.
- Monitor project progress, conduct technical reviews, and ensure alignment with organizational standards.
- Ensure optimal use of cloud infrastructure (GCP/AWS) and messaging systems for platform scalability.
- Provide hands-on leadership in backend technologies including multithreading and NoSQL databases.
- Conduct performance evaluations, coach engineers, and foster a high-performing team culture.
Skills Required
Java, Nosql, Gcp, Go, Python
Manager - Engineering - Data Engineering
Posted today
Job Viewed
Job Description
Skills: Engineering Manager with Bigdata/Fast Data, Power BI, Python, SQL
Experience: 12 to 16 Yrs
Lead and Mentor: Manage and mentor a team of Data Engineers, Data Analysts, and Business Analysts. Foster a collaborative and innovative team culture, ensuring accountability for performance and results. Set performance objectives, conduct performance reviews, and recommend pay actions.
Project Management: Oversee the planning, execution, and delivery of data projects. Ensure projects are completed on time, within scope, and within budget.
Vision and Strategy: Define a vision for the team in line with departmental strategy and operational challenges. Translate this vision into a concrete action plan, working with a high level of autonomy with some guidance from the Senior Manager.
Agile Methodologies: Implement and promote Agile methodologies within the team. Facilitate Agile ceremonies such as sprint planning, daily stand-ups, and retrospectives.
Collaboration: Work closely with Product Managers to understand requirements, prioritize tasks, and align development efforts with business goals.
Technical Direction: Provide technical direction and support to the team. Ensure best practices in data engineering, testing, and deployment are followed.
Quality Assurance: Ensure the delivery of high-quality data solutions by implementing robust testing and code review processes.
Continuous Improvement: Encourage continuous learning and improvement within the team. Stay updated with the latest industry trends and technologies.
Technical Excellence:
Production Support: Timely manage the investigation and resolution of production support issues and customer inquiries.
Collaboration: Collaborate with other development, architecture, solutions, and QA teams to ensure that data systems are designed for testability, stability, scalability, and performance.
Technical Proficiency: Proficiency in Power BI, Data Pipelines, Azure, and other relevant technologies. Experience with cloud platforms and exposure to other tech stacks like Python, SQL, etc.
Agile Expertise: Strong understanding and experience with Agile methodologies (e.g., Scrum, Kanban).
Leadership: Proven ability to lead and inspire a team. Excellent problem-solving and decision-making skills.
Cross-functional Collaboration: Experience working closely with Product Managers and other cross-functional teams.
Communication:
Team Communication: Ensure timely and appropriate communication to team members regarding company/organization information.
Stakeholder Communication: Maintain clear and effective communication with all stakeholders, including Product Managers, designers, and other development teams.