This role is part of our Central Data & BI Team at saas.group.We're looking for a Data Analyst to join our small Central Data & BI Team. Together, we look after the data warehouse, dbt models, and analysis that saas.group leadership, Finance, our acquisitions team, and our portfolio companies rely on. Most of the work happens in SQL and dbt rather than in reporting tools.The context changes a lot. Each of our portfolio companies has its own billing setup, data quirks, and questions. A large part of the work is due diligence on companies we're considering acquiring: taking data we've never seen before and turning it into figures that acquisition decisions rely on, often under a deadline.This is a hands-on role, but it isn't about typing as much SQL as possible. We already use AI agents extensively for implementation work. What we need is an experienced data person who can take an unclear business question to a result people can trust, question assumptions (including ours), and share real ownership of the platform. You'll be a sparring partner on approaches and trade-offs.This is an individual-contributor role without people management.Your immediate impact in the first 3-6 months will be:Get to know our data platform end to end, from ingestion with extract-and-load tools to transformation in dbt and the core SaaS metrics built on top, and start handling incoming data requests independentlyTake ownership of production data issues, working out whether an unexpected number reflects a real business change or a source, ingestion, or modelling problemDeliver model changes and analyses from the initial question to a validated result, working directly with our portfolio companies, Finance, and saas.group leadershipSupport due diligence on potential acquisitions by turning unfamiliar billing and customer data into reliable revenue and customer figuresYour responsibilitiesOwn requests end to end: clarify the question, assess the source data, investigate existing logic, build or change models, validate the result, and explain what it means and where its limits areBuild and maintain production dbt models for billing, subscriptions, customers, recurring revenue, retention, and related SaaS metricsBuild and maintain Metabase dashboards, reusable questions, and recurring reporting, alongside ad hoc analysisMonitor data quality and freshness, reconcile figures, and trace discrepancies back through transformation and ingestion to the source systemMaintain source integrations in Airbyte, including custom connectors, and onboard data from newly acquired companiesProcess unfamiliar and often incomplete billing, customer, and revenue datasets for due diligence on potential acquisitions, often under time pressureUse AI tools as a normal part of development, investigation, and documentation: frame the problem, provide the right context, review the output, validate it against real data, and keep sensitive data protectedBring an independent view to decisions about models, metrics, and priorities, and challenge assumptions when something doesn't add upDocument important definitions, source behaviour, limitations, and repeatable workflowsWhat You bring to the table3+ years in hands-on data roles where SQL, rather than spreadsheets or BI tools, was your main toolReal production experience building and maintaining data models with dbt or a similar code-based workflow, with version control and review, not just a course or side projectComfortable reviewing code, including in languages you don't write every day such as Python: you can tell whether it does what it should and whether a simpler solution would doExperience tracing data from a source system through ingestion and transformation into a business answer, and telling a genuine business change apart from a data problemSound analytical judgment and the habit of checking whether a result makes sense before you share itClear, direct communication with technical and non-technical stakeholders, and the confidence to push back and form your own viewOwnership of real outcomes: you prioritise independently, stay calm when production issues come up, and follow throughHands-on, daily use of AI tools (Claude Code, Codex, Cursor, or similar) in real data work, with the judgment to spot bad assumptions and verify the output yourselfCuriosity about unfamiliar systems: you don't need to know every tool we use, but you learn quickly and ask good questionsFluent written and spoken EnglishAble to work Central European hours, so you can collaborate with the team in real timeNice to have: SaaS subscription metrics such as MRR, ARR, churn, expansion, NDR, GDR, cohorts, and customer lifetime; billing systems such as Stripe, Chargebee, Recurly, or Paddle; PostgreSQL and Airbyte; understanding how APIs and data connectors work (authentication, pagination, rate limits, incremental syncs); supporting several products or business units with different source systems and definitions; acquisition due diligence or other work with unfamiliar datasets under time pressure.What’s in it for YouUltimate flexibility: We’re 100% remote. You can work from wherever you like, whenever you like.Freedom and autonomy: We’re a high-trust team, and you’ll be given lots of flexibility to solve problems in your own way — with plenty of help from the team when you need it.Minimum bureaucracy: We don’t like to get bogged down with meetings and red tape. We like to be efficient and keep momentum steady & sustainable.Small & friendly team: We help each other out, have fun, and joke around.Our network: We are a community of entrepreneurial SaaS professionals that regularly exchange ideas, knowledge, learning and expertise with each other internally.Flexible time off: We want you to recharge your batteries when needed.We believe in fair and transparent pay. Salary ranges at saas.group are location-adjusted, targeting local market medians for a remote-first environment, and will be shared with our potential future employees in writing before your first interview - so you have everything you need to evaluate the opportunity.
5 days ago