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Tier-1 brand, mid-level generalist role in Bangalore with broad skillset increases candidate competition.
Core data engineering skills are transferable, but Abinitio and banking compliance increase domain specificity.
Multiple mandatory 3+ year technology requirements plus explicit 4+ years experience.
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Lead moderately complex technology initiatives focused on large scale data processing frameworks and enterprise strategy deliverables.
Build, optimize, and maintain highly available data pipelines and oversee data integration including data modeling, data warehouse maintenance, and scripting for analysis.
Resolve moderately complex issues, lead teams to meet data engineering deliverables, and collaborate with colleagues to achieve strategic data engineering goals.
Minimum 4+ years of Data Engineering experience.
3+ years experience each with Spark, Ab Initio, Python or another scripting language, SQL, and data warehouse technologies.
Experience with Hadoop, Hive, Kubernetes, Docker, Google Big Query, Autosys, and data integration scripting is mentioned but not explicitly required as hard filters.
Notice period or location requirements: Not explicitly mentioned in the JD.
Experienced in end-to-end data engineering project execution and code reviews emphasizing testability and code coverage.
Comfortable working in Agile environments (Scrum or Kanban) and presenting to technical and executive audiences.
Familiarity with non-relational DBMS (MongoDB or Neo4j), real-time data streaming (Kafka), and Google Cloud Platform, with GCP Associate Cloud Engineer certification considered a plus.