About the role

Data Analyst using SQL, dbt, and Airbyte for saas.group’s SaaS portfolio analytics. Supporting production data quality, reporting, and acquisition due diligence.

Responsibilities

Join saas.group’s Central Data & BI Team
Learn the data platform end to end, from extract-and-load ingestion tools through dbt transformations and SaaS metrics
Handle incoming data requests independently
Own production data issues and distinguish business changes from source, ingestion, or modeling problems
Deliver model changes and analyses from initial question through validated result
Collaborate with portfolio companies, Finance, and saas.group leadership
Support acquisition due diligence by converting unfamiliar billing and customer data into reliable revenue and customer figures
Clarify questions, assess source data, investigate logic, build or modify models, validate results, and explain implications and limitations
Build and maintain production dbt models for billing, subscriptions, customers, recurring revenue, retention, and SaaS metrics
Build and maintain Metabase dashboards, reusable questions, recurring reports, and ad hoc analyses
Monitor data quality and freshness, reconcile figures, and trace discrepancies to source systems
Maintain Airbyte source integrations, including custom connectors, and onboard newly acquired-company data
Use AI tools for development, investigation, and documentation while protecting sensitive data
Challenge assumptions and contribute independent judgment on models, metrics, and priorities
Document definitions, source behavior, limitations, and repeatable workflows
Individual-contributor role without people management

3+ years in hands-on data roles where SQL was the main tool
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 Python, and assess correctness and simplicity
Experience tracing data from source systems through ingestion and transformation into business answers
Sound analytical judgment and validation of results
Clear, direct communication with technical and non-technical stakeholders
Ability to prioritize independently, remain calm during production issues, and follow through
Hands-on daily use of AI tools such as Claude Code, Codex, Cursor, or similar in real data work
Curiosity about unfamiliar systems and ability to learn quickly
Fluent written and spoken English
Ability to work Central European hours
Nice to have: SaaS subscription metrics knowledge, billing systems experience, PostgreSQL, Airbyte, APIs and data connectors, multi-product or multi-business-unit experience, and acquisition due diligence experience

100% remote work; work from wherever you like, whenever you like
Flexible, autonomous work environment
Minimal bureaucracy and efficient workflows
Small, friendly team environment
Internal network for exchanging ideas, knowledge, learning, and expertise
Flexible time off
Equal Opportunity Employer and inclusive workplace
Location-adjusted salary ranges targeting local market medians; salary range shared in writing before the first interview