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Senior, niche GenAI-data leadership at a Tier-1 bank in a metro yields moderate candidate density.
Mandatory finance domain knowledge and regulated reporting experience make cross-industry transferability low.
Explicit 10+ years, mandatory finance domain expertise, Snowflake and GenAI requirements drive strict filtering.
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Lead architecture, design, and implementation of enterprise-scale finance data platforms including data warehousing, analytics, and AI-powered solutions on cloud platforms such as Snowflake.
Drive GenAI and AI/ML integration for ETL automation, natural language interactions, RAG-based workflows, LLM orchestration, and agent-based AI within finance data systems.
Provide technical leadership and mentorship for data engineering teams while collaborating with cross-functional stakeholders to define and deliver data and AI strategies aligned with business goals.
10+ years of experience in data engineering or related roles with proven enterprise-level delivery.
Strong domain knowledge in finance, investment banking, or related industries.
Hands-on experience with cloud data platforms, preferably Snowflake, and building AI/GenAI enterprise data solutions including RAG and LLM orchestration.
Work Experience Required: At least 6 years relevant experience generally expected for required skills.
Experienced leader combining deep data engineering expertise with applied AI/GenAI architecture in regulated finance environments.
Operationally skilled in designing and governing safe, responsible AI solutions with strong evaluation frameworks and security controls.
Capable of managing global stakeholder relationships and driving adoption of innovative, scalable AI and data engineering practices in complex financial institutions.