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Tier-1 brand, popular Data Engineer title, mid-level experience, metro location, and broad skillset increase competition.
Core ETL, PySpark and SQL skills are transferable, but bank-specific compliance and ingestion patterns create moderate industry bias.
Explicit 4+ years requirement and mandatory PySpark, Oracle, SQL, and enterprise compliance needs make shortlisting stringent.
Lead moderately complex initiatives in enterprise-scale ETL and data engineering related to data processing frameworks and strategy deliverables.
Build and maintain optimized, highly available data pipelines supporting analytics, reporting, and data warehouse environments.
Oversee data integration tasks including developing data models, maintaining data warehouses, scripting for integration and analysis, and resolving moderately complex data engineering issues.
4+ years of Data Engineering experience or equivalent via work, training, education, or military experience.
4+ years of ETL development experience with hands-on PySpark development.
3+ years of experience working with Oracle database.
Proficiency in SQL (Oracle, SQL Server, Teradata) and experience with operational reporting, data validation, and troubleshooting ETL production issues.
Experienced in designing and optimizing complex SQL queries and developing scalable ETL pipelines using PySpark.
Familiarity with multiple data ingestion patterns including NDM file transfers, APIs, direct DB connections, and working knowledge of Linux environment.
Capable of translating requirements into technical specifications and collaborating to meet strategic data engineering goals within Agile Scrum workflows.