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Tier-1 employer, popular mid-level data role, metro location, and broad tech requirements raise competition.
Data engineering skills are transferable across industries but Ab Initio and banking compliance increase specialization.
Multiple explicit mandatory skills and 4+ years experience create strict technical filters.
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Lead moderately complex data engineering initiatives aligned with enterprise strategy deliverables.
Build and maintain optimized, highly available data pipelines and manage data integration work including data modeling, data warehouse maintenance, and scripting.
Resolve complex technical challenges and lead teams to meet data engineering deliverables in compliance with data policies and procedures.
4+ years of Data Engineering experience (work experience, training, military experience, or education).
3+ years experience each in Spark, Abinitio, Python (or other scripting language), SQL, and data warehouse technologies.
1+ years experience in each of Hadoop, Hive, Python, Kubernetes, Docker, and Google Big Query.
Experience working in Agile environment (Scrum or Kanban) and ability to conduct code reviews focusing on testability and coverage.
Demonstrated capability to lead data pipeline and data warehouse initiatives with strategic impact and compliance adherence.
Experienced in end-to-end data engineering project execution and presenting technical content to both technical and executive audiences.
Familiarity with cloud platforms (especially Google Cloud Platform), real-time streaming (Kafka), and non-relational databases (MongoDB or Neo4j) is a plus.