Senior Analytics Engineer

United States Digital Space LLC; Vancouver; On-site; CAD 120,000 - 180,000; Full time

Benefits offered by this job

Health insurance with dental

Breakfast and lunch catering

Home office setup budget

Generous compensation

Job summary

Asana's Data Science & Analytics team seeks a Senior Analytics Engineer who will own data foundations end to end, turning raw data into trusted datasets and defining business logic for KPIs.

Based in Vancouver with an office-centric hybrid schedule, you will collaborate across product, data science, and engineering to build certified dashboards and self-serve tools, while advancing AI-native analytics.

Qualifications

• 4+ years in analytics engineering or related role.
• Advanced SQL and data modeling fundamentals.
• Hands-on with a transformation framework (dbt) and orchestration (Airflow).
• Version control (Git) and modern warehouse/lakehouse platforms (Databricks).
• Data quality testing, observability, and data contracts experience.
• Domain fluency in at least one business area and cross-functional collaboration skills.

Responsibilities

• Own the Gold layer for a domain and design scalable data models.
• Implement canonical KPI logic and versioned metric marts.
• Build semantic layer and Genie spaces to enable self-service analytics.
• Maintain a single source of truth for KPI definitions and ownership.
• Define data contracts, SLAs, and ensure data quality and freshness.
• Create board-ready dashboards using governed Gold data with partners.

Skills

Advanced SQL

Data modeling

dbt

Airflow

Git

Databricks

Looker/LookML

Unity Catalog

Reverse-ETL

Tools

dbt

Airflow

Git

Databricks

Looker/LookML

Unity Catalog

Job description

Senior Analytics Engineer

The Data Science & Analytics team at the company 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 a Senior Analytical Engineer, you sit at the intersection of Data Engineering, Analytics, and Data Science, and you own the data foundations for a business domain end to end. Your mandate is to turn raw data into reliable, business-ready datasets that PMs, analysts, data scientists, and leaders actually trust and use — and to define the business logic and metric standards that make AI-powered self-serve trustworthy. You consume governed Silver tables and produce the Gold layer and semantic layer beneath the company’s most important metrics, dashboards, and Genie spaces.

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 your recruiter can share more about the in-office requirements.

What you’ll achieve

• Own the Gold layer for a given business domain (e.g., PLG funnel, marketing attribution, revenue, NPI/AWM): Design and continuously improve the curated, dimensional data models that downstream dashboards, Genie spaces, and ELT reporting depend on.
• Implement the canonical business logic behind your domain's core KPIs: Translate KPIs into governed, versioned metric marts that resolve "this number doesn't match" disputes for good.
• Build and curate the semantic layer and Genie spaces that power self-serve in your domain: Author the metadata, documentation, and prompt/metric definitions that let stakeholders query governed data in plain language through Claude and Databricks Genie.
• Own the metric dictionary for your domain: a single source of truth for what each metric means, who owns it, and where to find it. Partner with peers across DS&A to keep KPI definitions consistent where domains overlap.
• Author data contracts and SLAs at the Silver→Gold boundary, partnering with Horizontal Data Engineering on the inputs you depend on, and owning data quality, freshness, and oncall for Gold/metric-mart failures in your domain.
• Build and maintain certified, board-ready dashboards on governed Gold data, partnering with Data Science to translate insight requirements into trusted, reusable products rather than one-off builds.
• Partner directly with Product & Business, Data Science, and Engineering to turn ambiguous, underspecified questions into scalable datasets — anticipating downstream reporting impacts before they become incidents, and raising the data-model quality bar across the domains you touch.

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.
• 4+ years in analytics engineering, data engineering, or a closely related analytics role, with a track record of independently owning the data models a team relies on for decisions.
• Advanced SQL and strong data modeling fundamentals: dimensional modeling, star/snowflake schemas, slowly changing dimensions, and semantic layer design.
• Hands-on experience with a transformation framework (dbt or equivalent), orchestration tooling (e.g. Airflow), version control (Git), and modern warehouse/lakehouse platforms (Databricks experience preferred).
• Practical experience with data quality testing and observability, schema management and data contracts, and query/model performance and cost tuning.
• Demonstrated domain fluency in at least one business area (e.g. PLG funnels, SLG pipeline, marketing attribution, Product telemetry, revenue/ARR) and the judgment to translate "I don't trust this number" into a specific, durable model fix.
• Strong cross-functional partnership skills: requirement gathering, prioritization, documentation and enablement, driving alignment on metric definitions, and explaining technical tradeoffs to non-technical partners.
• Curiosity about AI-native analytics — NL2SQL, metadata/semantic layers for self-serve, and using tools like Claude and Genie to multiply your 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.

What we’ll offer

• Generous, transparent and fair compensation system (base salary and RSUs)
• Health insurance with dental
• Breakfast and lunch catering on the days that you work from the office
• Home office setup budget