Analytics Engineer, Finance and Modeling

This is a fully remote position, open to applicants in France.

📋 Description

• Take charge of metrics, reporting, and reconciliation to support financial decisions for four subscription and transaction-based brands.

• Implement governed definitions for ARR, renewal rate, churn, and CAC in dbt, and document these in Unity Catalog with defensible tests.

• Integrate metrics into the internal Slack AI agent for direct Finance inquiries.

• Transition recurring finance reporting into marimo, decommission underlying Tableau views, and automate scheduled runs.

• Reconcile transactions across app stores, payment processors, subscription systems, and the ledger.

• Develop automated discrepancy checks, escalate issues upstream with evidence, and convert discrepancies into tests.

• Forecast cohort subscriber and revenue projections, aggregate renewal and retention data, and provide insights for CFO forecasts and board reporting.

• Model LTV by acquisition source to assist with paid-spend allocation alongside Growth.

• Analyze pricing and promotional impacts prior to launches.

• Create churn propensity and uplift models when a retention process is ready to utilize the scores.

• Deliver models as tested, lineage-documented scored tables in dbt and Unity Catalog instead of notebooks.

• Support four brands and engage in diverse analytics, reconciliation, and dashboard tasks as required.

⛳️ Requirements

• 3+ years of experience in analytics engineering, data science, BI engineering, or advanced analytics.

• Experience with statistical modeling applied to business processes, including forecasting, survival or cohort analysis, or propensity modeling.

• Ability to evaluate the impact of a price change or growth experiment and provide honest interpretations of the results.

• Proven track record of building and defending subscription metrics to finance stakeholders, including ARR/MRR, renewal, churn, LTV/CAC, or cohort revenue.

• Proficiency in SQL and real dimensional modeling, with experience in designing data marts.

• Daily use of Python and Git as essential tools.

• Practical AI proficiency, including experience with Claude Code, coding agents, and agent SDKs.

• Willingness to manage multiple responsibilities within a small team environment.

• Preferred experience with dbt, Databricks, and Unity Catalog or a comparable lakehouse.

• Preferred background in reconciling transactional data to a financial system of record.

• Preferred experience with code-first notebook reporting using marimo, Hex, Streamlit, or Quarto.

🏝️ Benefits

• No explicit benefits or perks stated in the posting.