Data Analyst (SQL & dbt)

Role overview Join a small central data and BI team supporting leadership, Finance, acquisitions, and a portfolio of independent software businesses. The work centres on a SQL-and-dbt data platform rather than on reporting tools, and includes acquisition due diligence where unfamiliar billing and customer data must be turned into reliable figures under tight deadlines. It is an individual-contributor role that values ownership, sound analytical judgement, and the willingness to challenge assumptions.

Responsibilities - Own analytical requests end to end: clarify the question, assess source data, update models, validate results, and communicate what they mean and where their limits lie. - Build and maintain production dbt models covering billing, subscriptions, customers, recurring revenue, retention, and related SaaS metrics. - Develop Metabase dashboards and reusable reporting assets alongside ad hoc analysis. - Monitor data quality and freshness, reconcile figures, and trace discrepancies back through ingestion and transformation to the source system. - Maintain source integrations in Airbyte, including custom connectors, and onboard data from newly acquired businesses. - Support acquisition due diligence by processing unfamiliar, often incomplete billing and revenue datasets on deadline.

Requirements - Three or more years of hands-on data work where SQL was the primary tool, rather than spreadsheets or BI platforms. - Production experience building and maintaining data models with dbt or a similar code-based workflow, including version control and review. - Ability to review code in adjacent languages like Python and judge whether it does what it should. - Track record of tracing data from source systems through ingestion and transformation into a defensible business answer. - Sound analytical judgement with the habit of sanity-checking results before sharing them. - Clear, direct communication with both technical and non-technical stakeholders, and the confidence to push back. - Daily hands-on use of AI coding or analysis assistants, with the discipline to validate their output.

Nice to have SaaS subscription metrics such as MRR, ARR, churn, expansion, NDR, GDR, cohorts, and customer lifetime value; billing platforms like Stripe, Chargebee, Recurly, or Paddle; PostgreSQL and Airbyte; understanding of APIs and data connectors; working across multiple products with differing source systems; acquisition due-diligence experience.

Benefits and work setup Fully remote, with flexible hours and a small, low-bureaucracy team that values autonomy. Central European hours are expected so collaboration happens in real time. Compensation is location-adjusted, targeting local market medians for remote roles, and the range is shared in writing before the first interview.