> Markdown version of [/jobs/ext/2995858-data-engineer](https://www.wearedevelopers.com/jobs/ext/2995858-data-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer - **Company:** Viktor - **Location:** München, Germany - **Contract:** Permanent contract - **Skills:** BigQuery, Spreadsheets, Software as a Service, Python (Programming Language), PostgreSQL, Snowflake, Stripe, Slack, Vertica, Looker Analytics, Amazon Redshift - **Published:** September 19, 2026 - **Apply:** https://startup.jobs/data-engineer-viktor-7971191 ## About the Role * Experience taking ownership in a small, fast-moving team. * Familiarity with Stripe and SaaS metrics: MRR, ARR, NDR, LTV. You've helped close the books, not just queried them. * Background in ML or forecasting. Helpful, not essential. * You've worked where founders pulled their own numbers and you loved replacing that habit. ## Description The data foundation is already in use and still evolving. You improve the warehouse, pipelines, dashboards and alerts while keeping them dependable as the product and company change. You'll join our analytics function early, with no data lead above you. The foundation is in motion, not finished: you take real ownership of the warehouse, pipelines, dashboards, and alerts, and build them out. You report to Peter Albert. What You'll Actually Do * Own the ClickHouse warehouse end-to-end. Schema, ingestion, backfills, performance. You decide how it's structured and what gets in. * Build and maintain the pipelines. Prod Postgres, Stripe, Slack, ad platforms, whatever's next. You build and operate them, with tests, monitoring and safe backfills. You own the recovery when they fail and verify the data, not just that the job ran. * Run the BI layer. Hex dashboards for growth, finance, support, product. You build, maintain, and prune them; dead dashboards are worse than none. * Answer the questions that move the business. Retention cohorts, credit and unit economics, channel attribution, churn, pricing impact. You bring answers proactively. * Stand up monitoring and alerting. We hear about a metric moving the wrong way from your alerts, not from a customer. * Work with the co-founders and leaders across the company. You scope, prioritize, ship fast, and push back when the question isn't the right one. How You'll Know It's Working * The team makes decisions faster because the numbers are clear and trusted. * People stop building parallel spreadsheets. The dashboard is the source of truth. * When a metric moves, you knew first. * The co-founders stop pulling numbers themselves, because you're better at it. * New hires can answer most business questions without asking anyone. Who You Are * Metrics understanding. You understand what business metrics mean and how they are calculated. You reason about definitions, denominators, cohorts and segmentation, spot misleading comparisons, and connect metric changes to what is happening in the business. * Strong Python engineering for ingestion, transformations and orchestration. You build, test and maintain reliable pipelines, not just notebooks. * Agentic engineering is part of your daily workflow. You use coding agents to move faster while taking responsibility for correctness, maintainability and production behavior. * Familiar with columnar warehouses (ClickHouse, Snowflake, BigQuery, Redshift). Bonus for ClickHouse, since that's what we're on. * Built BI layers from scratch (Hex, Metabase, Looker). You know a dashboard that gets used from one bookmarked once and forgotten. * Product mindset. Proactive, challenges assumptions, biases toward action. * Founder mentality. You act like an owner of the function, not a ticket-taker in it. * Munich or Warsaw. Why This Role Is Different * No layers. No data lead above you. You own the foundation. * The work you ship defines how the company makes decisions. As the warehouse and BI layer improve, every team gets faster. * The questions are real: retention cohorts, credit economics, channel attribution at the unit level. The answers change what we do next quarter. * The co-founders already believe data is strategic. No convincing anyone it matters.