Senior Analytics Developer, People Analytics

What you'll do

• Design and build the data pipelines and transformation models that move raw data from source systems into a centralized data warehouse.
• Drive the creation of a canonical employee record with a stable, consistent identifier that survives job changes, rehires, and system migrations.
• Own the semantic layer for people metrics: define, document, and maintain agreed-upon definitions for core measures so that HR, Finance, and leadership are always working from the same numbers
• Bridge the gap between raw sources and business value. Ensure that data models are not just technically sound, but are purposefully built to answer the specific strategic questions for Wealthsimple
• Build slowly-changing dimension patterns and dated workforce snapshots that enable accurate point-in-time analysis.
• Establish data governance practices that belong in a people analytics function.
• Partner with HR business partners, Finance, and People Operations leaders to translate business questions into well-structured data models and durable analytical solutions
• Use AI tools to accelerate your work, drafting pipeline code, generating documentation, stress-testing metric logic, and turning technical findings into clear communication for non-technical partners

Skills you bring

• Python for pipeline orchestration, data transformation, and scripting
• Experience with dimensional modelling, SCD types 1/2/3, and snapshot patterns.
• Hands-on experience with dbt or equivalent, including testing documentations and incremental loading patterns.
• Pipeline orchestration using Airflow, Prefect, or similar.
• Familiarity with cloud data warehousing (Snowflake, BigQuery, or Redshift)
• Advanced SQL, including window functions, CTEs, date spine logic.
• HR data literacy: employee lifecycle events, job hierarchies, headcount types, and compensation structures
• Experience extracting data from various data platforms such as Workday, Ashby, or Greenhouse.
• Version control in Git as standard practice.

Nice to have

• Experience with identity resolution or entity matching — directly relevant to the golden record problem
• Familiarity with survey data platforms such as Qualtrics, Glint, or Culture Amp
• Exposure to workforce planning or headcount forecasting models
• Experience in a regulated or compliance-heavy environment, including familiarity with GDPR, CCPA, EEO reporting requirements

Who you are

• You're energized by building from scratch, you don't need a well-paved road to do good work, and you're not waiting for perfect requirements before you start
• You possess a "product owner" mindset. You don’t just deliver a table. You ensure the end-user understands the data, trusts it, and can use it to make decisions
• You take documentation seriously and hold a high bar for data quality without being precious about it. You ship, iterate, and improve rather than waiting for perfection before anything goes to production
• You bridge technical and non-technical worlds naturally.
• You think about privacy the way a good engineer thinks about security, as a design constraint, not an obstacle
• You're pragmatic about AI tools. You use them to move faster and document more thoroughly, and you know where they add value and where they don't