Wealthsimple

Senior Analytics Developer, Brokerage & Ledger Product Data Science

Job Description

This team sits at the operational core of Wealthsimple. We build the analytical foundation that powers how client activity is recorded, validated, executed, and reported across the business. Our work spans three closely connected domains:

Book of Record The authoritative historical record of all client financial activity. These datasets power virtually every client-facing metric at Wealthsimple. At our scale, small design decisions have outsized downstream impact.

Ledger Operations The internal systems and analytics that ensure the ledger is accurate, explainable, and trusted. This work partners closely with operations and CX teams to investigate issues, validate outcomes, and continuously improve data quality.

Brokerage, Capital Markets & Regulatory (BCMR) The back office of the trading platform. This includes datasets related to market maker interactions, brokerage feeds, margin, options, futures, and regulatory and compliance reporting. Accuracy and traceability here are non-negotiable.

The problems are interconnected and the data is shared. We’re hiring a Senior Analytics Developer to join the Brokerage & Ledger Product Data Science team. As a Senior Analytics Developer, you may work primarily in one of these areas, but the role is intentionally broad. You’ll own complex analytical datasets end-to-end, from raw inputs to well-designed, well-documented models that are trusted by product, operations, finance, and regulatory partners. You’ll be expected to operate with high autonomy, shape technical direction, and raise the bar for how analytics work is done.


In this role you will:
  • Design, build, and maintain high-quality analytical data models that support core brokerage and ledger workflows.
  • Own critical datasets that power client-facing metrics, operational decision-making, and regulatory reporting.
  • Work with large, complex, and often imperfect data sources, making trade-offs explicit and outcomes reliable.
  • Partner closely with product managers, engineers, operations, finance, compliance, and CX teams to understand stakeholder needs and translate them into durable data solutions.
  • Take a product-minded approach to analytics: designing datasets for clarity, usability, and long-term maintainability, not just correctness.
  • Establish and uphold standards for data quality, testing, documentation, and observability.
  • Use automation and modern tooling to reduce manual work and increase confidence in outputs.
  • Apply AI-assisted workflows thoughtfully to improve speed, quality, or insight generation, and clearly articulate where and why they add value.
  • Mentor and support other analytics developers through design reviews, code reviews, and informal coaching.
  • Communicate complex data concepts clearly, helping partners understand not just what the data says, but how to use it.

    • Role requirements:
  • Demonstrated experience working with large, complex analytical datasets in a production environment.
  • Strong SQL skills and experience building analytical models or data marts that are consumed by others.
  • Product-oriented mindset with a focus on data usability, consistency, and long-term ownership.
  • Experience collaborating with non-technical stakeholders and translating ambiguous questions into concrete analytical work.
  • Familiarity with modern analytics tooling such as dbt, Airflow, Python, and cloud data warehouses (e.g. Redshift, Snowflake). Deep expertise in every tool is not required.
  • Experience applying AI tools or techniques to analytics or data engineering workflows, with the ability to explain the impact clearly.
  • Comfort working in regulated or high-stakes environments where correctness, auditability, and trust matter.
  • Experience in financial services, trading, or accounting is a plus, but not a requirement.

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