Senior Manager, Analytics Engineering

Flexiti Financial Inc.; Toronto; Hybrid; CAD 170,000 - 200,000; Full time

Benefits offered by this job

Health & wellbeing resources

Paid vacation & sick days

Hybrid in-office work

Career growth opportunities

Community involvement

Inclusive, collaborative environment

Job summary

Questrade is seeking a Senior Manager, Analytics Engineering to define and execute the multi-year architecture for customer data. You will lead a lean, hands-on team to build a trusted 360-degree client view and an AI-native self-serve data ecosystem powering BI and autonomous agents.

You will bridge dbt, SQL, automated testing, CI/CD and cloud platforms with cross-functional partners across Analytics, Architecture, and upstream engineering to deliver scalable, governed data products.

Qualifications

• Bachelor’s degree or equivalent practical experience in a relevant field.
• 10+ years in analytics engineering or data platform development.
• Expert SQL and dbt with solid software engineering disciplines.
• Hands-on experience with production warehouses (BigQuery/Databricks/Snowflake).
• Experience designing production semantic layers for BI and AI agents.
• Proven track record leading engineers while staying hands-on.
• Experience with modern AI coding agents to accelerate workflows.
• Background in fintech, banking, or regulated data environments.

Responsibilities

• Architect and execute multi-year customer data architecture and analytics strategy.
• Define a scalable semantic layer and standardized metrics.
• Enforce software engineering best practices including CI/CD and testing.
• Lead complex data transformations with hands-on coding.
• Ensure data governance, observability, and security across warehouses.
• Collaborate with cross-functional teams on schemas and data change management.
• Mentor and grow analytics engineering teams with clear direction.
• Bridge analytics with data science, product strategy, and business analytics.

Skills

Advanced SQL

dbt

Software engineering

Code reviews

Orchestration pipelines

AI-enabled BI

Analytics engineering

Leadership

Data architecture

BigQuery

Databricks

Snowflake

Education

Bachelor’s degree in Computer Science, Software Engineering, Data Engineering, Information Systems, or equivalent

Tools

Git

Automated testing

CI/CD

dbt modeling

BigQuery

Databricks

Snowflake

AI coding agents

Job description

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.

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.

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.