Asana is hiring a Senior Analytics Engineer in Vancouver!
Asana is hiring a Senior Analytics Engineer for its Data Science & Analytics team in Vancouver. The position sits between data engineering, analytics and data science, and centers on owning the data foundations for a single business domain from start to finish — for example a product-led growth funnel, marketing attribution, revenue, or product telemetry. The core of the work is converting governed Silver-layer inputs into trusted Gold-layer dimensional models and a semantic layer that underwrites the company's most important metrics, dashboards and AI-assisted self-serve experiences. This is a hands-on, high-ownership role that combines modeling craft with metric governance and cross-functional partnership. The team works an office-centric hybrid schedule out of the Vancouver office, with in-office days standard on Monday, Tuesday and Thursday; Wednesday is typically a work-from-home day and Friday flexibility depends on the nature of the work.
Key responsibilities
- Own the Gold layer for an assigned business domain, designing and refining curated dimensional models used by dashboards, ELT reporting and Genie spaces.
- Encode core KPIs as governed, versioned metric marts that settle recurring disagreements about which number is correct.
- Build and curate the semantic layer and Genie spaces, authoring metadata, documentation and metric/prompt definitions that enable plain-language querying of governed data.
- Maintain the domain metric dictionary as a single source of truth covering definitions, ownership and discoverability, aligning with peers where domains overlap.
- Write data contracts and SLAs at the Silver-to-Gold boundary, and take ownership of data quality, freshness and on-call response for metric-mart failures.
- Produce certified, board-ready dashboards on governed Gold data, favoring reusable products over one-off builds.
- Partner with Product, Business, Data Science and Engineering to convert ambiguous questions into scalable datasets and to raise modeling standards across domains.
Key requirements
- 4+ years in analytics engineering, data engineering or a closely related analytics role, including independent ownership of decision-critical data models.
- Advanced SQL plus strong dimensional modeling fundamentals: star and snowflake schemas, slowly changing dimensions, and semantic layer design.
- Hands-on experience with a transformation framework such as dbt, orchestration tooling such as Airflow, Git, and a modern warehouse or lakehouse platform (Databricks preferred).
- Practical experience with data quality testing and observability, schema management and data contracts, and query/model performance and cost tuning.
- Demonstrated fluency in at least one business area such as PLG funnels, SLG pipeline, marketing attribution, product telemetry or revenue/ARR.
- Strong cross-functional skills: requirement gathering, prioritization, documentation, enablement, metric alignment and explaining technical tradeoffs to non-technical partners.
- Curiosity about AI-native analytics, including NL2SQL and semantic layers for self-serve; exposure to Unity Catalog, Looker/LookML or reverse-ETL tools is a plus.
- Seniority: Senior
- Work mode: Hybrid — office-centric in Vancouver, in-office Monday, Tuesday and Thursday
- Salary: $106,000 - $120,000 CAD annually (base)
- Key skills: SQL, Dimensional modeling, dbt, Airflow, Git, Databricks, Semantic layer design, Data quality and observability, Data contracts, Unity Catalog, Looker/LookML, NL2SQL
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