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Strong Tier-1 brand and metro location, but senior finance+GenAI specialization narrows candidate pool.
Mandatory finance and investment banking domain knowledge creates high industry specificity despite transferable technical skills.
Explicit 10+ years, mandatory finance domain experience, Snowflake and GenAI requirements impose strict selection filters.
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Lead architecture, design, and implementation of enterprise-scale data platforms and AI-powered data interaction solutions in finance technology.
Drive integration of GenAI, LLMs, AI/ML techniques for ETL automation, reporting, and intelligent data distribution.
Provide technical leadership and establish frameworks for AI solution evaluation, governance, and secure, responsible AI adoption in regulated finance environments.
10+ years in data engineering, architecture, or related roles with enterprise-level solution delivery.
Strong domain knowledge in finance, investment banking, or related industries mandatory.
Proven experience designing and implementing AI/GenAI solutions including RAG architectures, LLMs, prompt engineering, and AI integration with enterprise data platforms like Snowflake.
Work Experience Required: At least 6 years of relevant experience generally expected for required skills.
Experienced leader capable of managing and mentoring high-performing data engineering and AI teams in a global, financial technology environment.
Proficient in modern cloud data platforms (preferably Snowflake) and advanced AI and GenAI applications tailored for enterprise finance data.
Strategic thinker who can define and execute AI and data strategy with strong stakeholder management and delivery of complex projects under agile SDLC.