Senior Manager, Analytics Engineering
Role Overview
The Senior Manager, Analytics Engineering sets customer-data architecture, semantic-layer, and delivery strategy across Questrade.
The role leads a lean technical team while remaining hands-on, building a trusted customer view and an AI-enabled self-service data ecosystem.
The work combines data engineering with partnerships across Analytics, Architecture, and upstream engineering.
Key Skills for This Role
Full Job Posting
About Questrade Financial Group
QFG provides investment, foreign currency, wealth management, mortgage, real estate, and other financial services through its companies.
The organization describes its workplace as diverse, inclusive, collaborative, and hybrid.
Role overview
The Senior Manager, Analytics Engineering sets customer-data architecture, semantic-layer, and delivery strategy across Questrade.
The role leads a lean technical team while remaining hands-on, building a trusted customer view and an AI-enabled self-service data ecosystem.
The work combines data engineering with partnerships across Analytics, Architecture, and upstream engineering.
Responsibilities
- Set a multi-year customer-data architecture and platform roadmap that unifies client touchpoints into a high-integrity view.
- Build and maintain a governed semantic layer with standard metrics and business logic for BI and autonomous AI agents.
- Enforce dbt, modular SQL, CI/CD, code review, automated testing, and documentation practices.
- Lead greenfield implementations and critical data transformations through hands-on coding and modern coding agents.
- Implement governance, cost optimization, observability, and access controls; uphold privacy, security, and regulatory standards.
- Coordinate with data engineering, enterprise architecture, analytics, and upstream product teams on schemas, reliability, change management, and user needs.
- Direct, mentor, and grow analytics engineers and data specialists.
Required qualifications
- Bachelor’s degree in Computer Science, Software Engineering, Data Engineering, Information Systems, or equivalent practical experience.
- 10+ years in analytics engineering, data engineering, or data-platform development, including ownership of company-wide production data-warehouse architecture.
- Expert SQL and dbt, plus Git, automated testing, CI/CD, code reviews, and orchestration pipelines.
- Production warehouse architecture experience with BigQuery, Databricks, or Snowflake.
- Experience designing and maintaining production semantic layers for BI and programmatic consumers such as LLMs or AI agents.
- Track record leading and mentoring data or analytics engineers while remaining hands-on.
Additional qualifications
- Hands-on use of AI coding agents and ability to validate their output.
- Experience establishing data platforms, semantic layers, or engineering practices from the ground up.
- Fintech, banking, brokerage, or regulated customer-data experience.
- Ability to bridge analytics engineering with data science, product strategy, and business analytics.
Workplace
- Hybrid environment with at least three days in the office.
Compensation
- Base salary range is CAD 170,000–200,000; the final package depends on experience, skills, and location.
- Full-time permanent roles include a benefits plan and incentive program.
Benefits
- Benefits include health and wellbeing resources, paid vacation and personal and sick days, and career development opportunities.
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