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Job Description — Data Engineering Manager Role
Title
Data Engineering Manager
Experience
8–12 Years
Location
Mumbai/Pune/Bangalore/Hyderabad/Chennai - Hybrid Role
Overview
We are looking for a Data Engineering Manager to lead and drive execution for data engineering initiatives. This role combines technical leadership, delivery ownership, and hands-on data engineering expertise. The ideal candidate will manage a team of data engineers while actively contributing to data platform development, ensuring successful execution of data pipelines, release deliverables, and stakeholder expectations. This role bridges engineering leadership and hands-on data execution, enabling scalable and reliable data solutions.
Key Responsibilities
1. Team Leadership & Delivery Execution
Lead and manage a team of 8–10 data engineers.
Drive sprint execution, planning, and delivery tracking aligned with program release cycles.
Coordinate cross-functional execution across engineering and product stakeholders.
Remove delivery blockers and ensure timely completion of milestones.
Provide technical mentorship and guidance to engineers.
2. Hands-on Data Engineering
Contribute directly to development of data pipelines and data workflows (30–50% hands-on). Perform data analysis and SQL-based problem solving.
Design and optimize ETL/ELT pipelines.
Work with structured and enterprise data sources including SAP systems.
Support troubleshooting and performance optimization.
3. Data Platform & Engineering Ownership
Oversee development and maintenance of scalable data pipelines.
Ensure adherence to data engineering best practices and coding standards.
Maintain data quality, reliability, and operational stability.
Support data migration and integration initiatives.
4. Stakeholder & Program Collaboration
Act as the technical interface between engineering teams and program stakeholders.
Translate business requirements into executable technical tasks.
Support program release planning and execution readiness.
Communicate progress, risks, and technical decisions effectively.
Required Technical Skills
Strong expertise in SQL and data analysis
Experience building and managing ETL pipelines
Hands-on experience with:
PySpark
Postgres SQL or similar RDBMS
Azure cloud ecosystem (or equivalent cloud platforms)
Experience working with enterprise data flows (SAP or similar systems)
Data warehousing and data modeling fundamentals
Strong debugging and performance optimization skills Leadership & Functional Skills
Experience leading or mentoring engineering teams.
Ability to manage delivery execution in agile environments.
Strong stakeholder management and communication skills.
Experience coordinating across distributed teams.
Preferred Qualifications
Experience leading data transformation or migration initiatives.
Exposure to Databricks or modern lakehouse architectures.
Prior experience in enterprise-scale data programs.
Scrum/agile exposure (certification not mandatory).
Education Bachelor's or Master's degree in Computer Science, Engineering, or related field.
Role Success Indicators
Stable and predictable delivery of data initiatives.
Effective management of data engineering team execution.
High-quality, scalable data pipelines.
Strong collaboration between technical and program teams.
Job ID: 151089241
Skills:
data engineering , Java, S3, Hadoop, Scala, Big Data Technologies, Nodejs, Emr, Data Modeling, Redshift, Sql, Hive, Ec2, Spark, Python, AWS Tools, ETL pipelines
Skills:
Power Bi, Apache Spark, Databricks, Azure, Sql, Python, SODA or equivalent data quality observability tools, CI CD for data pipelines, Delta Lake, Atlan or similar data catalog and metadata platforms
Skills:
data engineering , Java, S3, Hadoop, Scala, Nodejs, Big Data Technologies, Emr, Data Modeling, Redshift, Sql, Hive, Ec2, Spark, Python, AWS Tools, ETL pipelines
Skills:
graph databases , Spark, Databricks, Sql, AWS, S3, Python, Tableau, Spark Streaming, dbt
Skills:
snowflake , AWS, Databricks, Sql, ELT, Etl, Python, Pyspark, Spark, GenAI