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Strong employer brand and metro location increase competition, but seniority and niche Databricks/Spark skills moderate it.
Databricks and Spark skills transfer across industries, but banking platform experience adds moderate domain sensitivity.
Explicit 10+ years and mandatory Databricks/Spark/Delta Lake/AWS expertise enforce strict filtering of candidates.
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Lead modernization and refactoring of legacy Hadoop pipelines to Databricks native architectures on AWS, enhancing scalability and performance.
Design and optimize Spark (JavaSpark/PySpark) applications using Databricks features such as Delta Lake, Autoscaling, and job orchestration workflows.
Contribute to architectural decisions, develop reusable components, and ensure solutions are scalable, maintainable, and production-ready with strong performance optimization.
10+ years of experience in data engineering or distributed systems.
Strong expertise with Apache Spark (JavaSpark/PySpark), Databricks on AWS, Delta Lake, and SQL.
Experience modernizing legacy data platforms to cloud-based AWS architectures and Spark performance tuning.
Bachelor's degree or equivalent experience.
Proven ability to translate high-level architecture into detailed technical designs and data pipeline models for complex systems.
Experienced in simplifying and optimizing large-scale batch processes in production environments.
Comfortable working collaboratively with architects, platform teams, and stakeholders in high-impact, time-bound projects.