Analytics Engineer
TL;DR:
Co-own Formula's entire analytics function alongside our Head of BI — half builder, half investigator, in one seat. This is not a data engineer and not a product analyst; it's the rare full-stack data person who makes both possible without a team in between, on a modern stack (Snowflake, dbt, Python, Dagster, Metabase) with AI woven into daily work.
What we're looking for:
- Someone who has been the strongest data person on a small team and is ready to do it again — with a co-owner mandate, not an executor seat.
- A pragmatic builder rather than a craft-obsessed engineer: ships the model that earns its keep, not the architecture diagram.
- A curious investigator who walks into the room with the answer, not the dashboard — and can push back on the question if it's wrong.
- Comfortable in a no-process environment: forms the request themselves, navigates ambiguity without hand-holding.
- Treats AI tools as a daily multiplier, not a novelty — already builds Claude / Cursor / GPT into how the work gets done.
What you'll be doing:
- Own and evolve the dbt project — design the data layer, write production models, optimize heavy queries, keep the warehouse honest.
- Build and run pipelines in Dagster across product, marketing (Facebook Ads, Google Ads, attribution), and finance sources.
- Run end-to-end analyses that change decisions in growth, product, marketing, and finance — from the question through the SQL to the recommendation.
- Co-design the analytics roadmap with the Head of BI: what we measure, what we automate, what we retire.
- Embed AI tooling into the analytical workflow to compound the team's output, not just tick a box.
Must have:
- Hands-on hybrid experience: personally written dbt models and personally run analyses that moved business decisions.
