Data Engineer

🎯 What You’ll Actually Do

• Build and run scalable pipelines (batch + streaming) that power gameplay, wallet, and promo analytics.

• Model data for decisions (star schemas, marts) that Product, BI, and Finance use daily.

• Make things reliable: tests, lineage, alerts, SLAs. Fewer surprises, faster fixes.

• Optimize ETL/ELT for speed and cost (partitioning, clustering, late arrivals, idempotency).

• Keep promo data clean and compliant (PII, GDPR, access controls).

• Partner with POs and analysts on bets/wins/turnover KPIs, experiment readouts, and ROI.

• Evaluate tools, migrate or deprecate with clear trade-offs and docs.

• Handle prod issues without drama, then prevent the next one.

🧠 What You Bring

• 4+ years building production data systems. You’ve shipped, broken, and fixed pipelines at scale.

• SQL that sings and Python you’re proud of.

• Real experience with OLAP and BI (Power BI / Tableau / Redash — impact > logo).

• ETL/ELT orchestration (Airflow/Prefect or similar) and CI/CD for data.

• Strong grasp of warehouses & lakes: incremental loads, SCDs, partitioning.

• Data quality mindset: contracts, tests, lineage, monitoring.

• Product sense: you care about player impact, not just rows processed.

✨ Nice to Have (tell us if you’ve got it)

• Kafka (or similar streaming), ClickHouse (we like it), dbt (modular ELT).

• AWS data stack (S3, IAM, MSK/Glue/Lambda/Redshift) or equivalents.

• Containers & orchestration (Docker/K8s), IaC (Terraform).

• Familiarity with AI/ML data workflows (feature stores, reproducibility).

• iGaming context: provider metrics bets / wins / turnover, regulated markets, promo events.

🔧 How We Work

• Speed > perfection. Iterate, test, ship.

• Impact > output. One rock-solid dataset beats five flaky ones.

• Behavior > titles. Ownership matters more than hierarchy.

• Direct > polite. Say what matters, early.

🔥 What We Offer

• Fully remote (EU-friendly time zones) or Bratislava if you like offices.

• Unlimited vacation + paid sick leave.

• Quarterly performance bonuses.

• No micromanagement. Real ownership, real impact.

• Budget for conferences and growth.

• Product-led culture with sharp people who care.

🧰 Our Day-to-Day Stack (representative)
Python, SQL, Airflow/Prefect, Kafka, ClickHouse/OLAP DBs, AWS (S3 + friends), dbt, Redash/Power BI/Tableau, Docker/K8s, GitHub Actions.

👉 If you know how to make data boringly reliable and blisteringly fast — hit apply and let’s talk.