Senior Data Engineer

Questrade is on a mission to help Canadians to become much more financially successful and secure.

For nearly 30 years, Questrade Financial Group has been delivering on that mission through investing, banking, mortgages, and real estate. Together, we tilt finance in favour of ambitious Canadians, creating new ways for them to seize the financial future they deserve.

We're looking for people who are ready to enter their career inflection point. Mission-driven, exceptional folks that never settle. The work here is hard because the responsibility is real. If that's the standard you've been looking for, keep reading.

Req #4401

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 Data Engineer

As part of the Brokerage Engineering organization, the Senior Data Engineer is accountable for the technical design, development, and operational excellence of scalable data pipelines and modern data platform infrastructure. Operating in a high-velocity, agile delivery model, this role bridges business requirements, core trading and brokerage operations, and downstream analytics to deliver timely, reliable, and audit-compliant data products. By leveraging cloud data warehousing, automated transformations with dbt (Data Build Tool), distributed data processing with Spark on Kubernetes, GCP data services, and Infrastructure as Code, the role enhances platform performance and data self-service capabilities across the brokerage ecosystem.

The mandate

In This Role, You Will

• Pipeline Architecture & Engineering: Lead the technical design, development, and optimization of scalable, high-performance batch and real-time streaming data pipelines (ETL/ELT), ensuring robust data ingestion, orchestration, compute efficiency, and timely availability for critical brokerage trading and digital investing platforms.
• Data Modeling & Transformation with dbt: Architect, implement, and maintain modular, version-controlled data models and transformation workflows using SQL and dbt, establishing robust automated testing, documentation, and data lineage to deliver analytics-ready and audit-compliant data assets.
• Distributed Data Processing & Spark Orchestration: Build, tune, and scale high-throughput big data processing workloads utilizing Google Cloud Dataproc and Apache Spark running on Kubernetes, optimizing cluster resource allocation, memory management, and job execution for complex brokerage datasets.
• Infrastructure as Code (IaC) & Cloud Provisioning: Provision, configure, and manage resilient cloud data infrastructure across environments using Terraform, embedding CI/CD automation, security best practices, and cost-effective resource management into all data platform deployments.
• Data Reliability, Observability & Incident Resolution: Analyze and resolve complex technical problems and production data anomalies across the stack, diagnosing root causes through systematic investigation and implementing durable monitoring, automated alerting, and self-healing solutions to prevent recurrence.
• Data Governance, Lineage & Regulatory Integrity: Ensure comprehensive data quality, data lineage, role-based access control, and metadata cataloging across all brokerage data pipelines to satisfy strict financial industry governance, auditability, and regulatory reporting standards.
• Cross-Functional Solution Delivery: Partner closely with Product Managers, Solution Architects, Software Engineers, and Data Science/ML Ops teams to translate complex business requirements and predictive models into robust, production-grade data products and integration workflows.
• Standards, Quality & Technical Mentorship: Define and enforce coding, testing, and deployment standards across data repositories, conducting thorough code reviews and providing technical guidance and mentorship to junior and intermediate engineers to foster engineering excellence.
  
  

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

• Bachelor’s degree in Computer Science, Software Engineering, Information Systems, or equivalent practical experience.
• 5+ years of progressive data engineering experience with demonstrated success delivering robust, production-grade data pipelines.
• Advanced proficiency in SQL and Python for data engineering, automation, and complex data transformations.
• Hands-on production experience with distributed data processing using Google Cloud Dataproc and/or Apache Spark.
• Demonstrated hands-on experience running and orchestrating data processing workloads on Kubernetes (containerization, pod scheduling, and resource scaling).
• Hands-on production experience with cloud data warehousing and orchestration platforms (e.g., Google Cloud Platform services such as BigQuery, Cloud Composer/Airflow, Dataflow, Pub/Sub, or Databricks).
• Demonstrated working knowledge and hands-on experience using dbt (data build tool) for data modeling, transformation, and automated testing.
• Demonstrated working knowledge of Infrastructure as Code (IaC) utilizing Terraform to provision, configure, and maintain cloud infrastructure.
• Strong experience with relational and non-relational database management systems (e.g., MSSQL, PostgreSQL, CloudSQL).
• Demonstrated experience with modern CI/CD deployment pipelines, automated testing frameworks, and version control (Git).
  
  

Nice to have

• Direct experience within financial services, brokerage technology, trading systems, capital markets, or wealth management data domains.
• Experience with event-driven or real-time streaming architectures (e.g., Apache Kafka, Google Cloud Pub/Sub).
• Relevant cloud or engineering certifications (e.g., Google Cloud Certified Professional Data Engineer, Databricks Certified Data Engineer, or Certified Kubernetes Administrator/Application Developer).
• Experience working within Agile/Scrum or Scaled Agile Framework (SAFe) environments.
• Practical experience leveraging AI-assisted developer tooling (e.g., Claude, GitHub Copilot, Cursor) to optimize development velocity and code quality.
  
  

Enter your career inflection point. Apply now.

LI-Hybrid,

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.

Base salary range

$123,000 - $143,000 CAD

Technology and AI

We mix human ingenuity with advanced technology. For ambitious builders like you, we provide the latest technology to enable your creativity. You'll have everything you need to build the best outcomes and products for our clients.

Diversity and Inclusion

At Questrade Financial Group of Companies, we’re committed to fostering a diverse, inclusive, and accessible work environment where individuals are treated with dignity and respect. Our global team reflects the diversity of the communities we serve and operate in.

Accessibility statement

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

AI in hiring

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