Manager - Data Engineering
Summary
Lead a team of data engineers to design and build scalable on-premise data pipelines using Python, Spark, SQL, and Airflow for robust ETL/ELT workflows.
We are looking for an experienced Manager – Data Engineering with 8+ years of experience in building and managing data engineering solutions in an on-premise environment. The ideal candidate should have strong hands-on expertise in Python, Apache Spark, SQL, and Apache Airflow, along with proven experience in leading data engineering teams and delivering scalable data pipelines.
Key Responsibilities
- Lead and manage a team of Data Engineers and provide technical guidance and mentorship.
- Design, develop, and optimize scalable data pipelines in an on-premise environment.
- Build robust ETL/ELT workflows using Python, Spark, SQL, and Airflow.
- Design and manage complex Apache Airflow DAGs for data pipeline orchestration.
- Develop and optimize Spark-based data processing solutions for large datasets.
- Write complex and optimized SQL queries for data extraction, transformation, and analysis.
- Troubleshoot pipeline failures, performance issues, and data quality challenges.
- Work closely with architects, business stakeholders, and cross-functional teams to understand requirements and deliver solutions.
- Conduct code reviews and ensure adherence to engineering and development best practices.
- Drive technical design, estimation, planning, and end-to-end project delivery.
- Monitor team performance, project timelines, risks, and dependencies.
- Mentor engineers and contribute to building a strong data engineering practice.
- 8+ years of overall experience in Data Engineering.
- Strong hands-on experience with Python.
- Strong experience with Apache Spark / PySpark.
- Advanced SQL skills, including complex joins, CTEs, window functions, subqueries, and query optimization.
- Strong experience with Apache Airflow for workflow orchestration and scheduling.
- Experience working with on-premise data environments.
- Strong understanding of ETL/ELT processes and data pipeline architecture.
- Experience handling large volumes of data and optimizing data processing workloads.
- Good understanding of data quality, monitoring, troubleshooting, and performance optimization.
Leadership Requirements
- Proven experience managing or leading Data Engineering teams.
- Strong stakeholder and client management skills.
- Ability to provide technical direction while managing project delivery.
- Experience with resource planning, task allocation, mentoring, and performance management.
- Strong communication and problem-solving skills.
- Ability to work in a fast-paced, Agile environment.
Good to Have
- Experience in large-scale enterprise data platforms.
- Experience with data warehouse concepts and data modelling.
- Experience with on-premise Hadoop/data ecosystems.
- Experience in migrating or modernizing legacy/on-premise data platforms.