Senior Data Platform Engineer

🎯 What You’ll Actually Do

• Architect and run high-load, production-grade data pipelines where correctness and latency matter.

• Design systems that survive schema changes, reprocessing, and partial failures.

• Own data availability, freshness, and trust - not just pipeline success.

• Make hard calls: accuracy vs cost, speed vs consistency, rebuild vs patch.

• Build guardrails so downstream consumers (Analysts, Product, Ops) don’t break.

• Improve observability: monitoring, alerts, data quality checks, SLAs.

• Partner closely with backend engineers, data analysts, and Product - no handoffs, shared ownership.

• Debug incidents, own RCA, and make sure the same class of failure doesn’t return.

This is a hands-on IC role with platform-level responsibility.

🧠 What You Bring

• 5+ years in data or backend engineering on real production systems.

• Strong experience with columnar analytical databases (ClickHouse, Snowflake, BigQuery, similar).

• Experience with event-driven / streaming systems (Kafka, pub/sub, CDC, etc.).

• Strong SQL + at least one general-purpose language (Python, Java, Scala).

• You think in failure modes, not happy paths.

• You explain why something works - and when it shouldn’t be used.

Bonus: You’ve rebuilt or fixed a data system that failed in production.

🔧 How We Work

• Reliability > elegance. Correct data beats clever data.

• Ownership > tickets. You run what you build.

• Trade-offs > dogma. Context matters.

• Direct > polite. We fix problems, not dance around them.

• One team, one system. No silos.

🔥 What We Offer

• Fully remote.

• Unlimited vacation + paid sick leave.

• Quarterly performance bonuses.

• Medical insurance for you and your partner.

• Learning budget (courses, conferences, certifications).

• High trust, high autonomy.

• Zero bureaucracy. Real engineering problems.

👉 Apply if you see data platforms as systems to be engineered - not pipelines to babysit.