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Tier-1 employer, popular Spark/Databricks role, metro location, and broad skill requirements create high competition.
Databricks, Spark and AWS skills are broadly transferable across industries, so background sensitivity is low.
Mandatory 8+ years plus required Databricks, Spark, Delta Lake and AWS skills make shortlisting highly strict.
Lead modernization and refactoring of legacy Hadoop Spark pipelines into Databricks native architectures on AWS.
Design, develop, and optimize scalable data processing solutions using Apache Spark (Java/PySpark), Databricks features, and Delta Lake.
Contribute to architectural decisions ensuring performance optimization, maintainability, and production readiness while collaborating with senior architects and platform teams.
8+ years of experience in data engineering or distributed systems.
Strong expertise with Apache Spark (JavaSpark/PySpark), Databricks on AWS, Delta Lake, and SQL.
Bachelor’s degree or equivalent experience.
Experience modernizing legacy data platforms to cloud-based architectures on AWS.
Proven ability to translate high-level architecture into detailed technical designs for data processing platforms.
Experience with Spark performance tuning and large-scale batch optimization in time-bound, high-impact environments.
Operates well within collaborative, multi-geography teams involving architects and DevOps, providing technical leadership on complex distributed systems.