Senior Data Engineer - AI Venture Capital - $180-250k Base

You set the data standards others build on, inside a firm that owns the AI transformation space end to end.

This is not a role where you inherit someone else's architecture and maintain it. You shape how data and knowledge move across an organization, build the platform primitives that get reused across engagements, and work shoulder to shoulder with AI Engineers, Applied AI Architects, and Measurement Scientists on problems that actually matter.

You carry real scope here. Both platform and client delivery sit in your remit, which means your decisions show up everywhere. You are not siloed into a single workstream or handed a backlog someone else defined.

The firm itself is founder-led and doing something genuinely different. It sits at the intersection of consulting, platform engineering, venture creation, and investment. It is the execution layer for enterprise AI transformation, and the model means incentives are aligned through ownership, not just fees.

Day to day you are building and operating production data pipelines, designing ETL and ELT workflows with proper schemas, data contracts, quality gates, and validation. You write Python and SQL to a production standard, without handholding. You understand vector search, RAG architectures, and how to structure context for LLMs. Security, access controls, and secrets management are second nature to you.

You think in systems. You see how data flows across a whole organization and design accordingly. Testing, monitoring, and documentation are part of your definition of done, not an afterthought. You are comfortable in client environments too. Discovery, scoping, clean handoffs, that is part of the job and you handle it well. You make architectural calls under time pressure, document the tradeoffs, and bring people with you.

Ready to be part of something at the start? Get in touch. No up-to-date CV required.