Senior Analytics Engineer

The Data Science & Analytics team at Asana handles transforming data into decisions by defining critical questions, surfacing answers, and embedding insights into major product and business decisions. The company is based in Warsaw with a hybrid office schedule.

• 4+ years in analytics engineering or related roles, owning critical data models.
• Advanced SQL and strong fundamentals in dimensional modeling, star and snowflake schemas, slowly changing dimensions, and semantic layer design.
• Hands-on experience with transformation frameworks like dbt, orchestration tools such as Airflow, version control systems (Git), and modern data platforms (preferably Databricks).
• Experience with data quality testing, observability, schema management, data contracts, and performance tuning.
• Domain fluency in areas such as PLG funnels, marketing attribution, product telemetry, or revenue metrics.
• Strong skills in requirement gathering, prioritization, documentation, metric definition alignment, and communicating technical trade-offs.
• Curiosity about AI-native analytics like NL2SQL, semantic layers for self-serve, and tools like Claude and Genie.
• Exposure to Unity Catalog, Looker/LookML, or reverse-ETL/activation platforms like Salesforce is a plus.

• Own the Gold layer for a business domain, designing and improving curated dimensional data models supporting dashboards and reports.
• Implement canonical business logic behind core KPIs, managing governed, versioned metric marts.
• Build and maintain semantic layers and Genie spaces to enable self-serve analytics via natural language querying.
• Manage the metric dictionary as a single source of truth for metrics' meanings, ownership, and locations.
• Author data contracts and SLAs for the Silver to Gold data boundary, ensuring data quality, freshness, and oncall support.
• Create certified, board-ready dashboards based on governed Gold data in partnership with Data Science.
• Collaborate closely with Product, Business, Data Science, and Engineering teams to convert ambiguous requests into scalable datasets and improve data model quality.

This position is based in Warsaw with a hybrid work schedule: office attendance on Monday, Tuesday, and Thursday, optional remote work Wednesday and possibly Friday depending on team requirements. The role requires English language proficiency. The employer encourages applications from diverse backgrounds, including candidates who may not meet all requirements.