Analytics Engineer

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.

• 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.

• 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.

• Hands-on hybrid experience: personally written dbt models and personally run analyses that moved business decisions.

• Strong SQL and ability to design a data layer from scratch.

• Statistical literacy you can defend — A/B testing, incrementality, correlation vs. causation handled correctly.

• Russian language for day-to-day work with the team.

Please note, while we are open to diverse experience and backgrounds, if you don't match "Must Have" criteria – we will not be able to consider your application.

• Experience in a solo or duo data team — no process, no committees, navigated the chaos yourself.

• Deep understanding of how paid acquisition works (Facebook Ads API, Google Ads, attribution modeling) where you actually moved CAC or LTV.

• Forecasting, financial modeling, or unit economics — especially LTV forecasting and cohort modeling.

• Production use of AI tools (Claude, Cursor, GPT) built into your routine, not just experimented with.

1. Inspiring Mission: Help users live longer, healthier lives through innovative products.

2. Impact: Directly influence company growth with minimal bureaucracy.

3. Attractive Compensation: Competitive salary and comprehensive benefits package.

4. Work-Life Balance: Flexible working hours.

5. Professional Development: Tuition reimbursement.

6. Remote Work: Fully remote, with a preference for candidates within ±2 hours of CET.

7. Benefits: Health insurance, gym membership reimbursement, home office support.