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Asana

Analytical Engineering Manager

Asana is hiring an Analytical Engineering Manager in Vancouver, Canada. It pays CAD 157k-CAD 178k a year and Level rates it ; you can apply on Asana.

Level's read on this job

  • On Level's scale, this role is Works on AI ●●●○: the daily work is on AI products, without building the model.
  • The posting mentions Claude, Databricks and Databricks Genie among its tools and skills.
  • Level classes it as a lead role.
  • Asana has 109 other open roles on Level.

AI in this role

Lead a team of analytical engineers building trusted data foundations and semantic layers that power AI self-service tools.

ClaudeDatabricksDatabricks Genie
analytical-engineeringdata-modelingsemantic-layerdata-governancemanagement
Analytical Engineering Manager

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. You sit at the intersection of Data Engineering, Analytics, and Data Science, and you are accountable for whether business stakeholders trust the data in your team's domains and can answer their own questions without routing through your team.

This role is based in our Vancouver office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday. Most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do and the teams with which you partner. If you're interviewing for this role, your recruiter will share more about the in-office requirements.

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.

At Asana, we're committed to building teams that include a variety of backgrounds, perspectives, and skills, as this is critical to helping us achieve our mission. If you're interested in this role and don't meet every listed requirement, we still encourage you to apply.

What we’ll offer

Our comprehensive compensation package plays a big part in how we recognize you for the impact you have on our path to achieving our mission. We believe that compensation should be reflective of the value you create relative to the market value of your role. To ensure pay is fair and not impacted by biases, we're committed to looking at market value which is why we check ourselves and conduct a yearly pay equity audit.

For this role, the estimated base salary range is between 157,000 - 178,000 CAD annually. The actual base salary will vary based on various factors, including market and individual qualifications objectively assessed during the interview process. The listed range above is a guideline, and the base salary range for this role may be modified.

In addition to base salary, your compensation package may include additional components such as equity, sales incentive pay (for most sales roles), and benefits. If you're interviewing for this role, speak with your recruiter to learn more about the total compensation and benefits for this role.

We strive to provide equitable and competitive benefits packages that support our employees worldwide and include:

  • Mental health, wellness & fitness benefits

  • Career coaching & support

  • Inclusive family building benefits

  • Long-term savings or retirement plans

  • In-office culinary options to cater to your dietary preferences

These are just some of the benefits we offer, and benefits may vary based on role, country, and local regulations. If you're interviewing for this role, speak with your recruiter to learn more about the total compensation and benefits for this role.

About us

Asana is a leading platform for human + AI collaboration. Millions of teams around the world rely on Asana to achieve their most important goals, faster. Asana has been named to Fortune's Best Workplaces for 7+ years and recognized by Fast Company, Forbes, and Gartner for excellence in workplace culture and innovation. We offer an exceptional office-centric culture while adopting the best elements of hybrid models to ensure that every one of our global team members can work together effortlessly. With 13+ offices all over the world, we are always looking for individuals who care about building technology that drives positive change in the world and a culture where everyone feels that they belong.

We believe in supporting people to do their best work and thrive. Our goal is to ensure that Asana upholds an environment where all people feel that they are respected and valued, whether they are applying for an open position or working at the company. We provide equal employment opportunities to all applicants without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by law.

Join Asana’s Talent Network to stay up to date on job opportunities and life at Asana.

How we rate this

Analytical Engineering Manager at Asana rates 60 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Analytical EngineeringData ModelingSemantic LayerData GovernanceManagementClaudeDatabricksDatabricks Genie

Questions you could be asked

  1. Tell me about a project where analytical engineering was part of your work. What did you do?
  2. Tell me about a project where data modeling was part of your work. What did you do?
  3. Tell me about a project where semantic layer was part of your work. What did you do?
  4. Tell me about a project where data governance was part of your work. What did you do?
  5. Tell me about a project where management was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: Analytical Engineering, Data Modeling, Semantic Layer, Data Governance, and Management. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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