Senior Analytical Engineering Manager

Asana Asana · Enterprise · Warsaw, Poland · Data

Lead a team of Analytical Engineers responsible for the data foundations (Gold layer, canonical metrics, dashboards, semantic layer) that enable trustworthy data and AI-powered self-serve analytics using tools like Claude and Databricks Genie. The role focuses on shipping trusted data products and enabling business stakeholders to answer their own questions.

What you'd actually do

  1. Lead, grow, and develop a team of Analytical Engineers: Own hiring, coaching, performance, and career growth, setting a high bar for data-model quality and stakeholder trust.
  2. Own the Gold layer and semantic-layer strategy across your team's domains (e.g. PLG, marketing, revenue, NPI/AWM), taking accountability for curated data models, canonical metrics, dashboards, and Genie spaces.
  3. Treat every recurring insight as a product with an owner, a cadence, and an SLA, building a catalog of trusted, versioned data products instead of one-off rebuilds.
  4. Drive self-serve enablement by prioritizing Gold tables, governed metric definitions, and metadata that make Claude and Databricks Genie trustworthy for stakeholders.
  5. Partner with Data Science, Data Engineering, Data Infrastructure, and business teams to author data contracts and SLAs at the Silver→Gold boundary, deciding what to build, automate, or sunset.

Skills

Required

  • SQL
  • data modeling
  • semantic layer design
  • dbt
  • Databricks
  • stakeholder management
  • people management
  • coaching
  • performance management
  • career growth

Nice to have

  • AI tools
  • emerging technologies
  • Claude
  • Databricks Genie
  • Unity Catalog
  • Looker/LookML
  • reverse-ETL/activation platforms

What the JD emphasized

  • 3+ years managing or leading a team of analytics engineers, data engineers, or analysts
  • A strong analytical-engineering technical foundation: advanced SQL, data modeling, semantic layer design, dbt or equivalent frameworks, and modern warehouse/lakehouse platforms (Databricks preferred).
  • A track record of shipping trusted data products (governed Gold tables, canonical metrics, semantic layers) that meaningfully reduce ad-hoc work and earn stakeholder trust.
  • Strong stakeholder management skills with senior cross-functional partners and leadership, with the ability to translate ambiguous business needs into clear roadmaps and explain technical trade-offs to non-technical audiences.