The RoleWe are looking for data engineers to build the data infrastructure that powers our mission of transforming how organizations understand and improve the Employee Experience. As one of the founding members of our new Toronto hub, this is a mid-to-senior role designed for someone who wants to build, not maintain - to design systems from scratch, set the standards, and watch other teams come to depend on what they ship.
You'll thrive here if you do your best work with true ownership and ambiguity rather than a fully-specified ticket, treating your data pipelines as products and your internal consumers as customers.
What You'll Do- Build the Data Foundation: Design and build scalable data pipelines that move, transform, and deliver high-quality data to AI, analytics, and product teams.
- Data Warehousing: Develop and maintain our data warehouse footprint and custom data models that serve as the structural foundation for employee experience insights.
- Platform Capabilities: Build shared data platform capabilities that make it faster, safer, and easier to deliver reliable data across the broader global engineering organization.
- End-to-End Ownership: Take pipelines from initial ingestion through transformation, testing, monitoring, and rigorous data quality validation.
- Cross-Functional Collaboration: Partner closely with the AI team, product engineering, and business analytics to get clean data into production in tight, iterative loops (idea prototype real-world use).
- Engineering Excellence: Help define how this new regional team executes data engineering-including practices, standards, and cloud architecture. Share what you learn and uplift the engineers around you.
What You Bring- Experience: 4+ years of experience building and operating production-grade data pipelines that cross-functional teams depend on.
- Python Mastery: Strong Python programming skills with a demonstrated ability to write clean, maintainable, and testable code.
- Data Modeling & SQL: Expert-level SQL and data modeling instincts. You can architect an enterprise warehouse layer from scratch and clearly articulate the why behind your schema design choices.
- Modern Data Stack: Hands-on experience with cloud data warehouses (Snowflake, BigQuery, or similar) alongside modern transformation and orchestration tooling (dbt, Airflow, or equivalents).
- Reliability Instincts: A genuine, proactive ownership instinct for data reliability, testing frameworks, and quality enforcement.
- Communication: Ability to make complex data platform initiatives legible to non-technical stakeholders.
Bonus Points:- You have designed data models or an entire warehouse layer from scratch, rather than only maintaining someone else's legacy setup.
- You have measurably improved the cost, performance, or reliability metrics of a production data platform.
- Note: We use Snowflake, AWS, and dbt, but we care much more about your foundational systems engineering capabilities and ability to learn than any specific tool familiarity.
Our Interview Process & AI TransparencyAt Perceptyx, we value your time and want our interviewers to be fully engaged in the conversation.
- Note-Taking: We use Metaview.ai to record and summarize our interviews. This allows our hiring team to focus on you rather than typing notes, ensuring a fairer and more accurate evaluation of your experience.
- AI Disclosure: While we use AI to assist in summarizing interview data, all final hiring decisions are made by Perceptyx employees. We do not use automated tools as the sole basis for selecting or rejecting candidates.
- Your Choice (Opt-Out): Participation in recorded interviews is voluntary. If you prefer not to have your interview recorded via Metaview, please notify your recruiter at the start of the session. Opting out will not negatively impact your candidacy.
Compensation & BenefitsSalary Range: $150,000-$190,000 CAD per year.
- Note: Final compensation is determined by factors including experience, geography, and skills.
- Benefits: Comprehensive medical, dental, and vision insurance; RRSP matching; generous PTO and paid holidays; parental leave; and professional development budget.
