Design, build, and maintain data models in dbt, with attention to grain, fact types, and modeling best practices.
Default to fixing problems at the right layer, even when a shortcut exists.
Develop and maintain the semantic layer in Looker—standardized metrics and reusable Explores over one-off fields—to support scalable analytics and AI-assisted workflows.
Partner with stakeholders to deliver scalable solutions—prioritizing reusable metrics and Explores over one-off artifacts, unless a bespoke solution significantly unblocks adoption.
Conduct end-to-end investigations when issues arise across the data stack (ingestion, modeling, BI, reverse ETL).
Work across adjacent tools including Snowflake, Segment, Amplitude, and Hightouch as needed.
Identify opportunities to improve data quality, reduce costs, and simplify the codebase.
Use AI tools daily for code generation, investigation, and documentation.
Enable AI-driven analytics (e.g., Snowflake Cortex, Looker conversational analytics) by optimizing the semantic layer and curating high-quality context for these systems.
Champion engineering best practices: version control, testing, clear documentation, and well-contextualized pull requests.

Requirements

Strong understanding of data modeling fundamentals: facts vs dimensions, grain, slowly changing dimensions, immutability.
Advanced SQL skills on a modern data warehouse platform (we use Snowflake).
Experience contributing to production analytics codebases (e.g., dbt) with reviews, testing, and conventions.
Comfort working in Looker or similar BI tools, with a focus on reusable patterns rather than one-off solutions.
Ability to engage proactively with stakeholders and communicate in business terms.
Willingness to spend time clarifying problems before jumping to solutions.
Daily use of AI tools, with appropriate review and validation of outputs.
Comfort working autonomously and making sound judgment calls - especially when you can’t get immediate input from the broader team due to timezones.
Nice to have: Snowflake performance tuning and cost awareness.
Experience with Fivetran, Segment, Amplitude, Hightouch, or similar tools.
Proficiency in Python for automation and scripting.
Familiarity with tracking plans and product analytics concepts.
Experience with reverse ETL workflows.
Exposure to AI-assisted analytics workflows or building lightweight internal automations.

Benefits

Employee share options from day one
RRSP program with employer matching
20 days of accrued annual leave/vacation plus 10 wellbeing days to prioritize yourself and your loved ones
Additional paid day off to celebrate your birthday, along with volunteering leave
Health, dental, and vision benefits starting immediately
Annual education allowance reimbursement to support your professional development
Employee recognition program
Quarterly wellness allowance to invest in your personal wellness
Paid subscriptions to Headspace and LifeWorks EAP
Flexible working arrangements, supported by WFH reimbursement and technology allowance to ensure your safety while working from home
Personal tax return assistance (since we're in the accounting business!)
Paid parental leave

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

data modelingSQLdbtLookerPythonreverse ETLdata quality improvementanalytics codebasessemantic layer optimizationAI-assisted analytics

Soft Skills

stakeholder engagementproactive communicationproblem clarificationautonomous worksound judgmentattention to detailcollaborationadaptabilitycritical thinkingengineering best practices