Description
The Data Science & Analytics team at Asana is how the company turns data into decisions , defining the questions that matter, surfacing the answers, and making sure insight is at the center of every critical product and business call.
As an Analytical Engineering Manager, you lead a team of Analytical Engineers who own the data foundations for the business: the Gold layer, canonical metrics, certified dashboards, and semantic layer that make Asana's most important numbers trustworthy, and that make AI-powered self-serve through Claude and Databricks Genie actually work.
What you'll achieve
- Lead, grow, and develop a team of Analytical Engineers: Own hiring, coaching, performance, and career growth, and set a high bar for data-model quality and stakeholder trust.
- Own the Gold layer and semantic-layer strategy across your team's domains (e.g. PLG, marketing, revenue, NPI/AWM): Your team is accountable for the curated data models, canonical metrics, dashboards, and Genie spaces the business depends on.
- Treat every recurring insight as a product with an owner, a cadence, and an SLA: Build a catalog of trusted, versioned data products instead of one-off rebuilds.
- Drive self-serve enablement: Prioritize the Gold tables, governed metric definitions, and metadata that make Claude + Databricks Genie trustworthy, so stakeholders can answer routine questions without coming to your team.
- Partner with Data Science, Data Engineering, Data Infrastructure, and business teams to author data contracts and SLAs at the Silver→Gold boundary, and decide what to build, what to automate, and what to sunset.
- Manage prioritization, run-rate, and cost as first-class metrics , making explicit build-vs-buy and stop-doing trade-offs rather than letting low-value work quietly erode the team's capacity.
About you
- Demonstrates curiosity about AI tools and emerging technologies, with a willingness to learn and leverage them to enhance productivity, collaboration, or decision-making.
- 3+ years managing or leading a team of analytics engineers, data engineers, or analysts, with a clear trajectory into people management.
- A strong analytical-engineering technical foundation that lets you set the bar: advanced SQL, data modeling and semantic layer design, dbt or an equivalent transformation framework, and modern warehouse/lakehouse platforms (Databricks preferred).
- A track record of shipping trusted data products , governed Gold tables, canonical metrics, and semantic layers , that meaningfully reduced ad-hoc work and earned stakeholder trust.
- Strong stakeholder management with senior cross-functional partners and leadership: translating ambiguous business needs into roadmaps, driving alignment on metric definitions, and explaining technical tradeoffs to non-technical audiences.
- Sound judgment on prioritization, sunsetting low-value work, and managing data cost and run-rate.
- Curiosity about AI-native analytics , NL2SQL, semantic layers for self-serve, and using tools like Claude and Genie to multiply your team's reach rather than replace rigor. Exposure to Unity Catalog, Looker/LookML, or reverse-ETL/activation (Salesforce, Marketo, Gainsight) is a plus.
What we'll offer
- The estimated base salary range is between 157,000 - 178,000 CAD annually.
- Our comprehensive compensation package includes additional components such as equity, sales incentive pay, and benefits.
- We strive to provide equitable and competitive benefits packages that support our employees worldwide, including mental health, wellness & fitness benefits, career coaching & support, inclusive family building benefits, long-term savings or retirement plans, and in-office culinary options.