Senior Analytics Engineer (AI)

Location: Vancouver office with an office-centric hybrid schedule; standard in-office days are Monday, Tuesday, and Thursday. Working from home is generally available on Wednesdays, while Friday requirements depend on the role.

Salary: $106,000–$120,000 CAD annually, plus potential equity and benefits.

Company

A leading platform for human-AI collaboration used by millions of teams worldwide, with an office-centric culture and a global presence.

What you will do

• Own and continuously improve curated Gold-layer dimensional models for a business domain such as PLG funnels, marketing attribution, revenue, or product analytics.
• Translate core KPIs into governed, versioned metric marts and maintain a single source of truth for metric definitions.
• Build semantic layers and Genie spaces with metadata, documentation, and prompt and metric definitions for self-serve analytics.
• Define data contracts and SLAs at the Silver-to-Gold boundary and own data quality, freshness, observability, and on-call support.
• Build certified, board-ready dashboards and partner with Data Science, Product, Business, and Engineering on scalable data products.
• Anticipate reporting impacts, resolve ambiguous data questions, and improve data-model standards across business domains.

Requirements

• 4+ years of experience in analytics engineering, data engineering, or a closely related analytics role.
• Advanced SQL and strong knowledge of dimensional modeling, star and snowflake schemas, slowly changing dimensions, and semantic-layer design.
• Hands-on experience with dbt or an equivalent transformation framework, Airflow or similar orchestration, Git, and modern warehouse or lakehouse platforms; Databricks is preferred.
• Experience with data-quality testing, observability, schema management, data contracts, and query and model performance optimization.
• Experience in at least one business domain, such as PLG funnels, sales pipeline, marketing attribution, product telemetry, or revenue and ARR.
• Strong cross-functional communication, requirements gathering, documentation, prioritization, and ability to explain technical trade-offs to non-technical partners.

Nice to have

• Experience with Unity Catalog, Looker or LookML, or reverse ETL and activation platforms such as Salesforce, Marketo, or Gainsight.
• Exposure to AI-native analytics, NL2SQL, Claude, or Databricks Genie.

Culture & Benefits

• Transparent and fair compensation with base salary and RSUs.
• Health and dental insurance, group life insurance, and fertility and family-forming support.
• Breakfast and lunch catering on office days.
• Home-office setup budget and MacBook with required accessories.
• Gym or fitness card and mental-health support.