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Strong Tier-1 brand, mid-level generalist data role, metro location, and broad skillset increase competition.
Core data engineering skills are transferable, but banking governance and controls increase domain specificity.
Mandatory 5+ years, specific Java/Python, data platform, orchestration and regulatory controls make filters stringent.
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Lead design and delivery of scalable, reliable data platforms and pipelines for critical use cases like analytics, search, and AI workflows.
Own building high-quality curated datasets with clear contracts, lineage, and measurable SLAs/SLOs ensuring security, privacy, resiliency, and auditability.
Maintain hands-on engineering including Java/Python development, batch/stream processing, orchestration (e.g., Airflow), and partner across teams to enable governed AI/ML capabilities.
5+ years of applied software engineering experience with recent leadership in data engineering and production pipeline delivery.
Proficiency in Java and Python for production-grade data systems including batch and streaming processing.
Strong advanced SQL skills with data modeling, schema design, and experience with pipeline orchestration tools like Airflow.
Experience building and operating data platforms with security, governance, and operational controls in regulated environments.
Experienced lead Data Engineer comfortable with both hands-on coding and cross-functional collaboration across engineering, product, UX, and compliance teams.
Strong applied knowledge of secure engineering practices, AI-assisted development tools, and responsible AI governance in software workflows.
Background in building scalable, high-throughput data processing solutions with operational excellence in regulated, complex enterprise settings.