• 10+ years building full-stack data products end-to-end, hands-on across a modern lakehouse stack (Databricks, Unity Catalog, dbt, Python, SQL) with recent work in a modern UI framework such as React (or equivalent); Databricks Apps experience a plus
• Direct experience embedding LLMs, retrieval-augmented generation, and agents into data engineering workflows, for example AI-assisted data quality, anomaly detection, or lineage tracing
• Track record as a hands-on technical leader or engineering manager for a high-performing team. You develop, mentor, and coach a talented, diverse team, and you create an inclusive, engaging environment where every engineer can thrive
• Track record operating production data platforms end-to-end - SLAs, data quality and contract enforcement, observability, cost, incident response, and CI/CD for data products serving demanding consumers
• Strong grasp of data modeling and data product design from source ingest to consumer-fit products, with shared metrics and dimensions that BI tools and agents can consume; familiarity with Databricks Genie, Unity Catalog metric views, or Open Data Contract Standard (ODCS) a plus
• Experience in Financial Services (ideally Investment Management), or a demonstrated ability to ramp quickly on complex regulated domains, with comfort partnering across product, business, risk, and platform stakeholders
• You bring high agency, curiosity, and resilience to ambiguous problems, exercise disciplined judgment on trade-offs between scope, speed, and quality, and communicate clearly across technical and business audiences
• Bachelor’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience