Overview
Lead Data Engineering & AI role in Finance Technology focused on designing and implementing enterprise-scale data platforms and AI-enabled data solutions.
What you'll do
- Architect and implement enterprise data platforms including data warehousing, semantic modeling, reporting, analytics, and data distribution.
- Drive adoption of GenAI/LLMs and AI/ML techniques for ETL automation, data enrichment, and intelligent data distribution.
- Build natural language-to-data and enterprise search capabilities over structured and unstructured finance data.
- Design RAG solutions integrating data sources, metadata, business rules, and contextual retrieval.
- Develop and govern LLM orchestration patterns including prompt design, tool usage, routing, context grounding, and secure integration.
- Lead agent-based AI solutions and evaluation frameworks for quality, grounding, latency, safety, explainability, and outcomes.
- Provide technical leadership and mentorship to data engineering team members.
What you'll need
- 10+ years of experience in data engineering, data architecture, or related roles.
- Deep expertise in SQL, data modeling, ETL, and scalable data pipelines.
- Strong hands-on experience with cloud data platforms, preferably Snowflake.
- Finance domain/functional knowledge in finance, investment banking, or related industries (mandatory).
- Experience designing and implementing AI/GenAI solutions including RAG architectures and LLM integrations.
- Hands-on experience integrating AI capabilities with enterprise data platforms, including Snowflake Cortex/agent patterns.
- Experience defining and operationalizing evaluation/testing frameworks for LLM-based applications.
Details
- Role is within the FRPPE Tech team in Finance Technology.
- Team leverages GenAI for finance productivity and data product development.
FullTime
Negotiable
Posted yesterday
10+ Years
