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Stay22, based in Montreal, helps creators and digital platforms monetize their traffic through background technology. The company serves 6,500+ creators and platforms with over $1 billion in annual transactions, expanding from travel into retail, lifestyle, publishing, events, and transport.
The Data team transforms raw data into trusted insights driving product and business decisions. As a Senior Analytics Developer, you will own the modelling and transformation layer that converts warehouse data into reusable data products. Modelling is central to your work: defining entities, grain, relationships, facts, dimensions, and governed metrics that stakeholders can trust.
You will partner with Product, Development, Analytics, and Business teams to solve problems and uncover opportunities—from improving user experience and product performance to increasing conversion, partner revenue, and operational efficiency. You'll translate these needs into semantic models and self-serve datasets and tools that help teams decide and act fast.
Key responsibilities include:
- Design, build, and evolve scalable analytical models and transformation workflows using SQL, dbt, Dagster, and modern warehouse patterns
- Define model grain, entities, keys, join paths, facts, dimensions, snapshots, incremental strategies, and materializations balancing usability, performance, and cost
- Translate business concepts into reusable metrics, semantic definitions, and analytical datasets for BI, experimentation, product analytics, and AI-enabled workflows
- Partner with Product, Development, Revenue, Marketing, Operations, and Analytics teams to identify business problems and opportunities including instrumentation, funnels, activation, engagement, conversion, retention, attribution, and revenue metrics
- Build and maintain reliable ELT and transformation workflows from internal and third-party sources, working closely with Data Development on ingestion and platform concerns
- Apply production development practices including data quality tests, freshness checks, observability, lineage, documentation, governance, version control, CI/CD, and automated validation to protect trust in analytical products
- Investigate product and business performance using reliable models and analysis to explain changes, identify opportunities, recommend next steps, and optimize performance, scalability, cost, and freshness
- Create machine-readable business context
- Use AI coding assistants and agentic workflows for exploration, SQL and Python scaffolding, refactoring, test generation, documentation, and impact analysis
- Validate AI-generated code and analytical logic through profiling, targeted tests, query results, lineage, impact and performance checks, and human review; retain human ownership of metric meaning, modelling, privacy, security, architecture, and production approval
- Mentor developers and analysts on modelling, SQL quality, metric design, testing, documentation, stakeholder discovery, and responsible AI-augmented development
This role combines advanced SQL and development practices with strong product and business acumen. You'll use AI-assisted and agentic coding tools to accelerate delivery while retaining human accountability for quality, security, correctness, and business meaning.
The company offers a prime Montreal location in Little Italy with cafeteria allowance, full gym access, and rooftop terrace with seasonal basketball/pickleball court and hockey rink. Benefits include health and dental coverage, RRSP matching, fully paid STM pass, and regular team socials, events, and retreats. Flexible schedules, work-from-anywhere opportunities, year-end shutdown, and flex days are available.
REQUIREMENTS:
- English proficiency required for daily communication with international colleagues and partners
- 5+ years of experience in analytics development, data development, BI development, or closely related role
- Advanced SQL skills and strong relational and dimensional modelling expertise, including grain, keys, joins, facts, dimensions, incremental processing, and performance trade-offs
- Hands-on experience building production transformation projects with dbt or comparable framework on modern cloud warehouse or lakehouse such as Snowflake
- Experience applying tests, documentation, lineage, version control, CI/CD, observability, governance, privacy, and access controls to analytical data products
- Demonstrated ability to define and govern business metrics, semantic models, and reusable datasets used by multiple teams or products
- Strong product and business acumen
- Proficiency in Python and AI-assisted or agentic development workflows, with judgment to validate outputs through testing, profiling, review, and business context
- Excellent communication and collaboration skills, including ability to explain modelling choices, analytical trade-offs, and data limitations to non-technical stakeholders
