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- Full-time
…outcomes, service performance, operational effectiveness, risk management, workforce readiness, and financial results. The role applies governance, produces decision-ready insights, and…
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Questrade Financial Group

Senior Manager, Analytics Engineering

Toronto, ON, Canada

Base salary range: $170,000 - $200,000

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Job details

Pay: Base salary range: $170,000 - $200,000
Posting language: English
Posted: Nov 5, 2026

Original job description

Questrade Financial Group (QFG), through its companies - Questrade, Questbank, Questrade Wealth Management, Community Trust Company, Zolo, and Flexiti, provides securities and foreign currency investment, professionally managed investment portfolios, mortgages, real estate services, financial services and more. We use cutting-edge technology to help Canadians become much more financially successful and secure.

At QFG, we combine human-centric collaboration with AI-driven innovation to redefine financial services. The ideal candidate will be a catalyst for change, using AI to transform and deliver unparalleled customer experiences and shaping a future where AI empowers our teams to do their best work.

Join our diverse, inclusive, and hybrid workplace to unleash your creativity and nurture your curiosity without limits. If you share this sense of infinite possibility, come shape your future at QFG.

What’s in it for you as an employee of QFG?

Health & wellbeing resources and programs
Paid vacation, personal, and sick days for work-life balance
Competitive compensation and benefits packages
Work-life balance in a hybrid environment with at least 3 days in office
Career growth and development opportunities
Opportunities to contribute to community causes
Work with diverse team members in an inclusive and collaborative environment

This job posting is for an existing vacancy.

We’re looking for our next Senior Manager, Analytics Engineering. Could It Be You?

This role will be responsible for:

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.

Need more details? Keep reading…

In this role, responsibilities include but are not limited to:

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.

So are YOU our next Senior Manager, Analytics Engineering? You are if you have…

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.

Additional kudos if you…

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.

Sounds like you? Click below to apply!

At Questrade Financial Group of Companies, with multiple office locations around the world, we are committed to fostering a diverse, inclusive and accessible work environment. This is an environment where individuals are treated with dignity and respect. Here, the unique skills and experience you bring will be valued. You will be supported and motivated, so that you can harness your unlimited potential. Our team reflects the diversity of the communities we serve and operate in. Having a collaborative and diverse team helps us push boundaries to bring the future of fintech into existence - not only for the benefit of our customers, but for those who build their career with us.

Questrade Financial Group of companies Applicant Tracking System utilizes artificial intelligence (AI) for application screening. The AI system operates on predetermined criteria, with final decisions subject to human review.

Candidates selected for an interview will be contacted directly. If you require accommodation during the recruitment/selection process, please let us know and we will work with you to meet your needs.

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More about this job

Responsibilities

The Senior Manager, Analytics Engineering defines and executes the multi-year architecture and delivery strategy for customer data while leading a high-performing technical team. This role bridges modern data engineering rigor with cross-functional partnerships to build an AI-native self-serve data ecosystem.

Requirements

Candidates must have a bachelor's degree and over 10 years of progressive experience in analytics or data engineering with expertise in SQL, dbt, and production data warehouses. A proven track record in technical leadership and architecting semantic layers is required.

Skills

Analytics Engineering
Data Engineering
SQL
dbt
BigQuery
Databricks
Snowflake
Data Architecture
Semantic Layer
CI/CD
Data Governance
Data Observability
Leadership
Mentoring
AI Enablement
Business Intelligence

Benefits

Health and wellbeing resources
Paid vacation
Personal days
Sick days
Competitive compensation
Benefits packages
Career growth and development opportunities

Visa sponsorship

Not detected in the job text

Keywords

Analytics Engineering
Data Engineering
SQL
dbt
BigQuery
Databricks
Snowflake
Data Architecture
Semantic Layer
CI/CD
Data Governance
Data Observability
Fintech
Business Intelligence
AI Agents
Git
Automated Testing
Data Modeling
Cloud Data Platforms
Software Engineering
Leadership
Mentoring
Data Strategy
Customer Data
Regulatory Standards
Data Security
Pipeline Orchestration
Greenfield Implementation
Data Warehouse
AI-driven Innovation

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