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Strong employer brand, metro location, and broad data/GenAI requirements increase applicant competition.
Core data engineering skills transferable, but bank HR domain and governance needs raise moderate domain sensitivity.
Explicit 7+ years plus wide mandatory technical stack and regulatory expectations drive strict filtering.
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Lead design, architecture, and delivery of scalable, secure data engineering solutions for HR data ecosystem, enabling advanced analytics and AI-driven insights.
Act as a technical advisor to senior leadership influencing technology decisions, architecture, and strategy enterprise-wide.
Drive AI/GenAI adoption, mentor engineering teams, and ensure data modernization aligns with business priorities and compliance.
7+ years of engineering experience (includes work experience, training, military experience, education).
7+ years of hands-on data engineering experience including data platform migration to cloud-native lakehouse architectures.
3+ years of experience transforming legacy data frameworks to modern stacks on private or public cloud platforms like Azure Fabric or GCP.
Strong expertise in SQL, Python, distributed data frameworks (Spark, Beam), cloud-native architectures, data governance tools (Collibra, Alation, Purview), and AI/GenAI technologies.
Senior-level engineer with proven ability to influence enterprise-wide data engineering and AI strategy and architecture.
Experienced hands-on technologist balancing innovation with operational stability and regulatory compliance in large organizations.
Strong cross-functional collaborator familiar with HR data challenges and leading large, complex data modernization and AI-enabled initiatives.