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 up-to-date 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.

📌 DATA ENGINEERING MANAGER (Mumbai)
🏢 Zemoso Technologies
📍 Mumbai