Design & deliver modular, production-grade data models : Translate raw data into well-tested, performant datasets and reusable building blocks for downstream consumers (analytics, dashboards, ML).
Build and govern the semantic layer : Define and maintain standardized business metrics and semantic objects so teams and AI systems share a single source of truth.
AI data strategy & unstructured data tooling : Design data lifecycles for AI use cases—ingestion, embedding, RAG, and model-centric data plumbing—and convert unstructured signals (transcripts, documents, emails) into AI-ready assets.
Model observability & lineage. Implement monitoring, lineage, and auditability so we can trace what data influenced an analytic or AI output and detect data quality regressions.
Governance & cross-team enablement. Partner with Data Engineering, RevOps, Product, and other stakeholders to set modeling standards, manage dbt access and ownership boundaries, and enable “self-service” analytics across the company.
Engineering best practices. Apply software engineering principles to the data stack: dbt or similar transformation frameworks, Git, CI/CD, environments (dev/stage/prod), testing, and code review.
Mentorship & standards. Help grow the team by setting modeling standards, reviewing peer work, and mentoring junior modelers/analysts.

5+ years experience in data architecture, data modeling, analytics engineering, or a related role building production data models and semantic layers.
SQL expert. Able to write efficient, maintainable SQL for complex transformations and to optimize performance in a cloud warehouse.
Hands-on experience with dbt (or equivalent) and Git/CICD for data transformations and model deployment.
Proven track record designing metrics/semantic layers and ensuring a “single source of truth” for business definitions.
Experience with observability & lineage tooling, or designing data quality and audit processes for analytic/ML outputs.
Strong cross-functional communication skills; comfortable translating ambiguous business questions into reliable data artifacts and enabling non-technical consumers.

Competitive, equitable salary with top-tier health benefits, dental, and vision insurance
Hybrid work environment, with expectation for local Clions (Vancouver, Calgary, Toronto, Dublin, London, New York City and Sydney) to be in office min. twice per week.
Flexible time off policy, with an encouraged 20 days off per year.
$2000 annual counseling benefit
RRSP matching and RESP contribution
Clioversary recognition program with special acknowledgement at 3, 5, 7, and 10 years

Data Architect

Key skills