Senior Data Engineer
Summary
Lead a team of 8-10 data engineers while spending 30-50% of time hands-on building ETL/ELT pipelines using PySpark, SQL, and Azure cloud, working with enterprise data sources like SAP.
Role : Data Engineering Lead / Manager
Experience: 8–12 Years
Mode of work : Hybrid
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).
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.
Education :
Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.