Senior Data Engineer
Prevalent AI (company site, opens in a new tab)5–7 yrsKochiOn-siteDirect career pageEst. 10–16 LPA
Posted 16h ago
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Job description
Structured overview of role & requirements
About This Role
- Develop, test, and maintain efficient production-grade PySpark applications focusing on complex transformations and scalable solutions.
- Diagnose performance bottlenecks and optimize Spark workloads using deep knowledge of Spark internals including execution plans and resource utilization.
- Own end-to-end engineering problems including implementation, testing, deployment and collaboration with stakeholders for reliable batch and incremental data pipelines.
Minimum Requirements
- 5–7 years of relevant software or data engineering experience with substantial hands-on PySpark development.
- Strong proficiency in Python programming and PySpark for production-grade distributed data processing.
- Deep understanding of Apache Spark internals, including execution, shuffle behavior, partitioning, and parallelism.
- Strong SQL skills including joins, aggregations, window functions, and query optimization fundamentals.
Ideal Candidate Profile
- Expertise in writing efficient PySpark code with strong ability to diagnose and resolve performance bottlenecks using Spark UI and execution plans.
- Experience owning complex Spark engineering problems independently from design through production delivery.
- Comfortable with advanced Spark optimization techniques such as AQE, join strategies, partition tuning, and resource management.