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Job description

Exp - 7-12yrs Work location ; Bangalore Work Mode : Hybrid • Role: Senior Data Engineer Spark/PySpark/Scala/Hive | Experience: 7+ years | Location: Bangalore, Hybrid • Design, develop, deploy, and support enterprise-scale Data Lake and distributed processing solutions using Spark, PySpark, Scala, Python, Hive, Spark SQL, and Airflow. • Build modular, testable, reusable ETL pipelines across HDFS, Hive, Parquet, and Cloudera CDP on-premises environments. • Apply partitioning, bucketing, schema evolution, data quality, reconciliation, error handling, monitoring, recovery, and security practices. • Optimize workloads through expertise in joins, shuffles, serialization, caching, partition sizing, file formats, query plans, and resource utilization. • Implement data modeling, CI/CD, Git, GitLab, Jenkins, Maven/SBT, release, and operational practices. • Troubleshoot logs, failures, performance bottlenecks, and production incidents through effective root-cause analysis. • Demonstrate strong conceptual depth, coding discipline, analytical thinking, and attention to detail. • Communicate clearly, challenge assumptions, learn rapidly, and convert ambiguity into pragmatic outcomes. • Own customer-facing delivery with a Forward Deployed Engineer mindset: adaptable, hands-on, action-oriented, and accountable. • Use Claude, Cursor, and Copilot responsibly for coding, testing, automation, and documentation.

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