Senior Manager - Analytics Engineering

The return on your career investment

• Compensation and incentives built to reward the value you bring.
• RRSP matching of up to 6%.
• Health and wellness resources and programs, including $5,000 in mental health practitioner coverage.
• $5,000 in tuition subsidies for job-related courses, every year.
• 100% parental top-up, up to 26 weeks for birthing parents and 18 weeks for non-birthing parents.
• A hybrid environment, with at least three days in the office built for working together.
• Paid vacation, personal, and sick days.
• A community care day to give back to the causes you care about.

This job posting is for an existing vacancy.

We’re looking for our next Senior Manager, Analytics Engineering

The Senior Manager, Analytics Engineering defines and executes the multi-year architecture, semantic layer, and delivery strategy for customer data across Questrade. Leading a lean, high-performing technical team while remaining actively hands-on, this role establishes a single, trusted 360-degree view of the client and builds an AI-native self-serve data ecosystem that powers business intelligence and autonomous agents. The role bridges modern data engineering rigor—spanning dbt, SQL, automated testing, CI/CD, and cloud data platforms—with close cross-functional partnerships across Analytics, Architecture, and upstream engineering to deliver scalable, secure, and governed data products.

The mandate

In this role, you will:

• Architecture & Technical Strategy: Set the multi-year customer data architecture and analytics engineering vision, translating enterprise priorities into a scalable platform roadmap that unifies diverse client touchpoints into a single, high-integrity view.
• Semantic Layer & AI Enablement: Architect and maintain the enterprise semantic layer, establishing standardized metric definitions, business logic, and governed models that empower self-serve BI tools and autonomous AI agents to deliver consistent, trusted answers.
• Engineering Rigor & Quality Standards: Define, champion, and enforce software engineering best practices within analytics—including robust dbt modeling, modular SQL, automated CI/CD pipelines, code reviews, automated testing, and comprehensive data documentation.
• Hands-On Delivery & Prototyping: Directly lead complex, greenfield implementations and critical data transformations by writing high-quality code and leveraging modern coding agents to drive execution speed and technical excellence.
• Data Governance, Observability & Security: Implement strict data governance, cost optimization, data observability, and access controls across the data warehouse, ensuring customer data models adhere to privacy, security, and regulatory standards.
• Cross-Functional Collaboration & Stakeholder Alignment: Partner closely with Central Data Engineering, Enterprise Architecture, Analytics & Insights, and upstream data product teams to align on schemas, pipeline reliability, data change management, and end-user requirements.
• Team Leadership & Capability Building: Direct, mentor, and grow a high-performing team of analytics engineers and data specialists, providing clear technical direction, continuous coaching, and an environment of high accountability and continuous learning.

You’re ready for this mandate if you have the following qualifications

• Bachelor’s degree in Computer Science, Software Engineering, Data Engineering, Information Systems, or equivalent practical experience.
• 10+ years of progressive experience in analytics engineering, data engineering, or data platform development, including owning the architecture of a company-wide production data warehouse.
• Expert-level SQL and dbt, paired with solid software engineering disciplines (Git, automated testing, CI/CD, code reviews, and orchestration pipelines).
• Deep hands-on experience architecting and maintaining production warehouses on BigQuery, Databricks, or Snowflake.
• Demonstrated track record designing and maintaining production semantic layers that serve business intelligence and programmatic consumers (LLMs / AI agents).
• Proven track record leading and mentoring data engineers or analytics engineers while remaining actively technical and hands-on.

Nice to have

• Regular hands-on experience using modern AI coding agents (such as Claude Code) to accelerate development workflows, with an understanding of where these tools fail and how to validate their output.
• Experience establishing new data platforms, semantic layers, or engineering practices from the ground up in a fast-paced or greenfield environment.
• Background in fintech, banking, brokerage, or regulated customer data environments.
• Demonstrated ability to bridge technical analytics engineering with data science, product strategy, and business analytics.

Compensation Information

• Base salary range: $170,000 - $200,000
• The final compensation package will be commensurate with the successful candidate's experience, skills, and geographic location (Canada). It includes a comprehensive benefits plan and a competitive incentive (bonus) program for Full-Time Permanent roles.

Enter your career inflection point. Apply now. 

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Base salary range 170000 - 200000 CAD