data
Posted Apr 23Senior Analytics Developer, People Analytics
at Wealthsimple
(canada), CanadaHybrid
Responsibilities
- BUILD SOMETHING PEOPLE LOVE Wealthsimple's mission is to help everyone achieve financial freedom – by making financial services simple, transparent, and low-cost.
- - 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.
Requirements
- The People Analytics team is a new function.
- You'll be the first members of the People Analytics team, which means you're not inheriting a system: you're designing one.
- - 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 -