Senior Analytical Engineering Manager

Asana operates a Data Science team that informs strategy through experimentation, causal inference, statistical and machine learning techniques, and data storytelling. The Analytical Engineering Manager leads a team maintaining the Gold layer, canonical metrics, certified dashboards, and semantic layer to ensure trustworthiness of key business data. This role intersects Data Engineering, Analytics, and Data Science and is based in Asana's Warsaw office, following a hybrid office-centric schedule.

• Minimum 3 years managing or leading teams of analytics engineers, data engineers, or analysts.
• Strong analytical-engineering technical foundation including advanced SQL, data modeling, semantic layer design, and frameworks like dbt.
• Experience with modern warehouse/lakehouse platforms, preferably Databricks.
• Proven track record of delivering trusted data products such as governed Gold tables and canonical metrics.
• Strong stakeholder management skills translating business needs into roadmaps and explaining technical trade-offs.
• Skilled in prioritization, managing data cost, and sunsetting low-value work.
• Curiosity about AI-native analytics tools, including NL2SQL, Claude, Genie, Unity Catalog, Looker, and reverse-ETL/activation platforms.

• Lead, grow, and develop a team of Analytical Engineers, including hiring, coaching, and career growth.
• Own the Gold layer and semantic-layer strategy across team domains such as PLG, marketing, revenue, and NPI/AWM.
• Maintain curated data models, canonical metrics, dashboards, and Genie spaces.
• Treat recurring insights as products with owners, cadence, and SLAs.
• Drive self-serve enablement prioritizing Gold tables and governed metric definitions for AI tools like Claude and Databricks Genie.
• Partner with Data Science, Data Engineering, Data Infrastructure, and business teams to author data contracts and SLAs.
• Manage prioritization, run-rate, and cost, making build-vs-buy and trade-off decisions to protect team capacity.

This role is based in Warsaw with an office-centric hybrid schedule requiring presence on Monday, Tuesday, and Thursday, with optional work from home on Wednesday and conditional work from home on Friday.