Data Modeller (12 Month Contract)

Clio; Burnaby; Hybrid; CAD 90,000 - 125,000; Full time

Benefits offered by this job

Hybrid model

Competitive compensation

Equity

RRSP matching

Wellness programs

Job summary

Clio is seeking a Data Modeller to join our Data Insights and Business Operations teams. Based in Canada, Vancouver, Calgary, or Toronto, this role focuses on designing, building, and maintaining scalable data models using dbt to support analytics, dashboards, and AI-ready datasets.

You will partner with Product, Revenue Ops, Finance, and Data Engineering to translate business questions into trusted data, ensure data quality, and promote governance.

Qualifications

• 2–4 years of analytics engineering or data modeling experience.
• Strong SQL and database fundamentals with backend data modeling focus.
• Experience with dbt or similar transformation framework is an asset.
• Familiarity with cloud data warehouses (Databricks, Redshift, Snowflake).

Responsibilities

• Design, build, and maintain scalable data models for analytics and AI-ready data products.
• Collaborate with Product, Revenue Ops, Finance, and Data Eng to translate requirements.
• Develop automated tests, monitoring, and data quality validation.
• Contribute to governance, standards, and documentation for analytics ecosystem.

Skills

SQL

dbt

Data modeling

Analytics engineering

Python

Looker

Tools

dbt

Looker

Databricks

Snowflake

GitHub Copilot

Job description

• We are currently seeking a Data Modeller to join our Business Operations Team. This role is available to applicants based in Vancouver, Calgary, or Toronto


• Our Data Modelling team is part of the broader Data Insights Team. We build trusted, scalable data products that empower teams across Clio to make informed decisions. By transforming complex data into reusable, well-governed models, we enable self-service analytics, operational reporting, product insights, and emerging AI initiatives


• Esign, build, and maintain scalable data models: Transform raw and complex data into well-tested, reusable data models using dbt (or similar tools) that support analytics, dashboards, operational reporting, self-service analytics, and AI-ready data products


• Partner with stakeholders and communicate clearly: Collaborate with Product, Revenue Operations, Finance, Data Engineering, and business stakeholders to translate business questions into trusted datasets, and present technical concepts and findings in a way that is clear and actionable for both technical and non-technical audiences


• Ensure data quality and reliability: Develop automated tests, monitoring, and validation to ensure data freshness, schema stability, and logic accuracy, and to proactively resolve data quality issues


• Promote data modeling best practices: Contribute to standards, documentation, and governance that improve consistency, scalability, and long-term maintainability across the analytics ecosystem


• Leverage AI to improve productivity: Use AI-powered development tools and assistants to accelerate data modeling, improve code quality, and contribute to AI-ready data pipelines and workflows

Benefits

• Specialized learning and development programs and access to an in-house performance coach


• Equitable compensation for your contributions, regardless of gender, race, or any other identifying factor


• Access to pay transparency on all of our global roles


• Company equity for applicable employees


• RRSP-matching in Canada, 401k in the US, and pension plans in Ireland


• Hybrid model – striking the right balance between the benefits of in person connectivity that in office brings, and the flexibility of remote


• Flexible paid time off (4-week minimum with opportunities for personalization based on individual needs and achievements)


• Parental leave options for birthing and non-birthing parents


• A $500 contribution to your child’s RESP


• Various health, dental, and vision benefits for you and your family, including an Employee and Family Assistance Program


• Virtual and In-person Wellness Programs to support mental and physical health


• Paid time for volunteering through our Clio Gives program


• $2000 annual counseling benefit for CAD Clions

We are looking for someone who is passionate about data and enjoys solving business problems through thoughtful, scalable data solutionsYou thrive in a collaborative, fast-paced environment and are excited to partner with technical and non-technical stakeholders to make data more accessible, trustworthy, and actionableYou are curious, detail-oriented, and continuously looking for ways to improve how data is modelled, governed, and consumed. You enjoy learning new technologies—including AI-powered development tools—and applying them to improve productivity and deliver better outcomesAbility to translate business requirements into reusable data models and collaborate effectively with technical and non-technical stakeholdersFluency working with AI-powered development tools—such as VS Code, Claude Code, and similar assistants—and the ability to apply skills, agents, and automation to accelerate data modeling workExperience building data models with dbt or a similar transformation framework is an asset, though not required if you bring strong SQL and database fundamentalsSolid understanding of dimensional modeling and data warehousing concepts, with familiarity working in cloud data warehouses (e.g., Databricks, Redshift, or Snowflake)2–4 years of experience in analytics engineering or data modeling, ideally in SaaS, building and maintaining production data models from raw source data across multiple systemsDeep SQL skills and hands-on experience working directly in databases and data warehouses, with Python or a similar language an asset. This role is focused on the backend modeling layer rather than visualization or dashboard buildingExperience with Looker or other modern BI platformsExperience implementing data quality testing and monitoring frameworksExperience supporting self-service analyticsExperience working with AI-assisted development tools such as GitHub Copilot, Cursor, or similar technologiesExposure to building data products that support machine learning or generative AI applications