Job Description
Responsibilities
- Design and evolve the data models that power analytics, operational use cases, and AI/ML across thousands of studios.
- Help raise the bar on data reliability — embed governance, testing, and lineage so both people and AI systems can trust the numbers by default.
- Partner with product, and other engineering teams to turn ambiguous business problems into robust data solutions.
- Evaluate and evolve new approaches with us — data mesh patterns, and emerging AI tooling — and help decide what genuinely earns a place in our stack.
- Grow into our financial and regulatory reporting workstream (Finion Capital), where correctness and auditability matter most.
Your profile
- 3+ years in data engineering with a focus on data warehousing — and the appetite to take on more ownership than you’ve held so far.
- Strong SQL and Python for data work.
- Working with AI tools feels natural to you — and, just as important, the judgment to review and validate what they produce. You treat AI output as a draft to verify, not an answer to trust, especially where correctness is non-negotiable.
- A solid grasp of data architecture and modeling principles (dimensional modeling, slowly-changing dimensions, incremental patterns) — or the drive to deepen it fast.
- Hands-on experience with dbt on a cloud warehouse — this is where you’ll live day to day.
- Working knowledge of relational and some exposure to non-relational Databases (DynamoDB, MongoDB).
- A track record of debugging tricky data issues and shipping durable fixes.
- Excellent written and verbal English
Are you interested in this position?
Apply by clicking on the “Apply Now” button below!
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