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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.
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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.