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Tier-1 brand, popular data engineer title, mid-level experience, metro location increase applicant competition.
Medium because ETL, SQL and Python skills transfer broadly, but banking governance adds domain specificity.
High due to explicit years plus mandatory Informatica, Python, Oracle, VLDB and ETL production experience.
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Lead moderately complex data engineering initiatives impacting large-scale data processing frameworks and enterprise strategy.
Design, build, optimize, and maintain scalable ETL/ELT data pipelines and data integration workflows, ensuring data quality and governance compliance.
Oversee production environment support including monitoring, troubleshooting, performance tuning, and incident resolution while collaborating with cross-functional teams.
Minimum 4 years of Data Engineering experience demonstrated via work/training/military/education.
Minimum 4 years of IT experience with expertise in ETL development, Data Integration, Informatica PowerCenter/IICS, Python, UNIX/Linux, Shell scripting, and advanced SQL with Oracle database experience.
Experience with Very Large Databases (VLDBs), job scheduling tools like AutoSys, and familiarity with data governance, metadata management, and data lineage.
Experience leveraging generative AI tools (GitHub Copilot, Devin AI, or similar) to improve code quality and productivity.
Experienced operating in large enterprise environments requiring adherence to data quality, governance, and compliance standards.
Comfortable designing and optimizing complex ETL/ELT pipelines and production support within Agile teams.
Demonstrated ability to integrate modern cloud data platforms (e.g., GCP, MongoDB) and distributed processing frameworks (Apache Spark) alongside traditional enterprise tools.