Описание
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.
Задачи
•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
Требования
•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
Условия
•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
