data analyst for SaaS metrics

saas.group acquires promising B2B SaaS companies and develops them as part of a portfolio of 25 software brands. Its Central Data & BI Team supports the group’s leadership, Finance, acquisitions team, and portfolio companies with data warehousing, analytics, and due diligence.

• Own data requests end to end: clarify questions, assess source data, investigate existing logic, build or change models, validate results, and explain their meaning and limitations;
• Build and maintain production dbt models for billing, subscriptions, customers, recurring revenue, retention, and related SaaS metrics;
• Build and maintain Metabase dashboards, reusable questions, and recurring reports, and conduct ad hoc analysis;
• Monitor data quality and freshness, reconcile figures, and trace discrepancies through transformations and ingestion back to source systems;
• Maintain source integrations in Airbyte, including custom connectors, and onboard data from newly acquired companies;
• Process unfamiliar and often incomplete billing, customer, and revenue datasets for acquisition due diligence, often under time pressure;
• Use AI tools in development, investigation, and documentation by framing problems, providing context, reviewing outputs, validating them against real data, and protecting sensitive data;
• Bring an independent perspective to decisions about models, metrics, and priorities, and challenge assumptions when something does not add up;
• Document important definitions, source behavior, limitations, and repeatable workflows;
• Learn the data platform end to end, from ingestion through dbt transformations to core SaaS metrics, and handle incoming data requests independently;
• Take ownership of production data issues and determine whether unexpected figures reflect business changes or source, ingestion, or modeling problems;
• Deliver model changes and analyses from the initial question to a validated result, working directly with portfolio companies, Finance, and saas.group leadership;
• Support due diligence on potential acquisitions by turning unfamiliar billing and customer data into reliable revenue and customer figures.

• 3+ Years of hands-on data experience, with SQL as the primary tool rather than spreadsheets or BI tools;
• Production experience building and maintaining data models with dbt or a similar code-based workflow, including version control and review;
• Ability to review code, including in languages such as Python, and assess whether it works as intended or could be simplified;
• Experience tracing data from source systems through ingestion and transformation to business results, and distinguishing business changes from data issues;
• Sound analytical judgment and habit of checking results before sharing them;
• Clear, direct communication with technical and non-technical stakeholders, and confidence to challenge assumptions and form an independent view;
• Ability to prioritize independently, stay calm during production issues, and follow through;
• Daily hands-on use of AI tools such as Claude Code, Codex, Cursor, or similar in real data work, with the judgment to identify bad assumptions and verify outputs;
• Curiosity about unfamiliar systems and ability to learn quickly and ask good questions;
• Fluent written and spoken English;
• Ability to work Central European hours and collaborate with the team in real time;
• Nice 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 of APIs and data connectors, including authentication, pagination, rate limits, and incremental syncs; experience supporting several products or business units with different source systems and definitions; acquisition due diligence or other work with unfamiliar datasets under time pressure.

• Salary ranges are adjusted by location and target local market medians for a remote-first environment; salary details will be shared in writing before the first interview;
• Flexible time off;
• Flexible work schedule.