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.