- 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.
- 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.
- 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.
- 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.
- 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.
Skills Required
- 4+ years experience building and operating production-grade data pipelines
- Strong Python programming skills with clean, maintainable, testable code
- Expert-level SQL and data modeling instincts; ability to architect enterprise warehouse layers
- Hands-on experience with cloud data warehouses (Snowflake, BigQuery, or similar)
- Experience with modern transformation and orchestration tooling (dbt, Airflow, or equivalents)
- Proactive ownership for data reliability, testing frameworks, and quality enforcement
- Ability to communicate complex data platform initiatives to non-technical stakeholders
- Designed data models or an entire warehouse layer from scratch
- Measurably improved cost, performance, or reliability of a production data platform
- Experience with AWS
What We Do
Perceptyx combines employee surveys and people analytics in a way that not only helps you see more of what’s going on in your organization, but also helps you see how to drive the organization forward. Too many surveys only focus on measurement, with overly prescriptive models that don’t offer a fresh perspective on the challenges facing your business. And they rarely connect the dots between the employee experience and business outcomes, making it difficult to know which actions will have the greatest impact. With a solution fully tailored to your specific organizational needs, Perceptyx makes it possible for organizations to see more clearly, see the bigger picture, and see the next steps. It’s why nearly one-third of the Fortune 100 already rely on Perceptyx and why 95% of the organizations that come to us stay with us. - Perceptyx. See the way forward.









