Senior Analytics Engineer

Senior Analytics Engineer responsible for building reliable analytics systems, managing data pipelines, and providing self-serve data products for teams.

Requirements

• 5+ years in analytics engineering, data engineering, BI engineering, or data platform roles with ownership of production analytics systems.
• Expert SQL: data modeling, warehouse transformations, query optimization, dependency analysis, and reusable metric and dataset design.
• Strong Python: API extraction, automation, data validation, scripts, tests, and production-friendly pipeline code.
• Hands-on experience with workflow orchestration such as Airflow, including DAG design, task dependencies, retries, backfills, and operational debugging.
• Strong understanding of data quality, lineage, observability, and incident-style response for stale, broken, or inconsistent analytics data.
• Strong BI and dashboard skills, preferably Metabase, with ability to design dashboards that are self-explanatory, reliable, and tied to decisions.
• Practical understanding of SaaS, product, and business metrics: funnels, activation, TTV, retention and cohorts, churn, revenue, CAC, LTV, and NRR.
• Comfortable working with operational data such as availability, incidents, latency, errors, and pipeline health, with ability to model and report it accurately with engineering teams.
• AI-native working style: comfortable using AI tools for coding, analysis, documentation, and automation, with strong judgment about validation and production safety.
• Strong cross-functional communication: can align technical and non-technical teams on data definitions, tradeoffs, ownership, and what should or should not be measured.
• Excellent written and verbal English.

Benefits

• Competitive salary in USD
• Stock options
• Cutting-edge technology
• Flexible schedule
• Global fast-growing market
• Multinational team