Senior Data Operations Engineer (Toronto)

Position Title:

Senior Data Operations Engineer

Department:

Business Intelligence

Status:

Full-time/Permanent

Location:

Toronto, ON (Hybrid)

Company Description The Canadian Football League is Canadas home for professional football. With over a century of rich history and nine member teams across the nation, the CFL provides world‑class entertainment and excitement to a passionate and dedicated fan base. A season‑long journey of unforgettable moments and must‑see‑TV broadcasts culminates in Canada’s largest single‑day sporting event – the Grey Cup, where the newly crowned champions earn the right to hoist the iconic emblem of Canadian football. The CFL is dedicated to entertaining fans in Canada and abroad. The league pursues that goal through a continuing commitment to modernise and elevate the game and the business. The CFL is transforming its digital ecosystem and maximising fan engagement through captivating content, data analytics, personalised marketing, and more. The CFL proudly champions the values upon which Canada was built – unity, diversity, inclusion, strength, and service to the community. The league is supportive of all peoples, cultures, and backgrounds, offering a respectful and inclusive working and playing environment, centred on acceptance and understanding.

Position Summary We are seeking a skilled and passionate Data Operations Engineer with at least 4 years of experience. In this role, you will design, build, and maintain robust, scalable, and productive data pipelines on AWS infrastructure. You will leverage your expertise in Terraform for infrastructure‑as‑code, Python for pipeline development, and SQL for data transformation. You will work closely with the stakeholder groups of marketing and sales to ensure they have timely, correct, and informative data. The ideal candidate is a problem‑solver with a strong technical foundation in data engineering principles, AWS cloud services, and automation.

Key Responsibilities

Build and optimise ETL/ELT pipelines to ingest, transform, and load data from various sources into and out of our data lake and data warehouse.

Utilise Python and SQL to develop efficient and scalable pipeline logic.

Implement data quality checks and monitoring within pipelines to ensure data accuracy and reliability.

Troubleshoot data flow issues.

Optimise underperforming pipelines.

Design, provision, and manage AWS infrastructure for data pipelines using Terraform.

Automate infrastructure deployments, updates, and scaling using GitHub and Terraform.

Develop and evolve Snowflake pipelines and data structures.

Work with various AWS services including (but not limited to): S3, EC2, EMR, Lambda, Step Functions, and RDS.

Ensure security and compliance best practices are implemented across AWS infrastructure.

Communicate pipeline status, performance, and issues to stakeholders.

Participate in code reviews and contribute to improving data engineering best practices.

Document pipeline designs, infrastructure configurations, and operational procedures.

Stay up to date with the latest trends and technologies in data engineering, AWS cloud services, Terraform, and Python.

Identify opportunities to improve existing pipelines and infrastructure for efficiency, scalability, and reliability.

Contribute to the development of data engineering standards and best practices within the team.

Qualifications & Skills

Bachelors degree in Computer Science, Engineering, or a related field.

4 or more years of professional experience in data operations, data engineering, or a similar data‑focused role.

Background must show supporting a specific infrastructure through multiple lifecycles.

Proven experience designing, building, and maintaining data pipelines for large‑scale datasets.

Strong proficiency with AWS cloud platform and experience with a wide range of AWS data services (e.g., S3, EC2, Lambda, Step Functions, RDS).

Demonstratable expertise with SQL.

Solid experience in Python or similar programming for data engineering tasks and pipeline development.

Experience with Terraform for infrastructure‑as‑code and automating AWS infrastructure deployments.

Understanding of data warehousing concepts, ETL/ELT processes, and data modelling principles.

Experience with data pipeline monitoring, performance tuning, and troubleshooting.

Familiarity with version control systems.

Strong problem‑solving and analytical skills.

Excellent communication and collaboration skills.

Expected Compensation The expected compensation range for this position is $75,000‑$90,000, which includes base pay plus bonuses and variable incentive pay, if eligible. This range represents a good faith estimate for this position and should serve simply as a guide. The specific compensation offered may vary based on factors such as candidate experience, skills, budget, location.

Other Considerations

Hybrid Model: The incumbent will be required to attend the office in accordance with the CFL Hybrid Work Policy. In addition, you are required to attend meetings and other business events at the office or other venues as business needs dictate.

Work Schedule: Due to the nature of the business, the incumbent must be available and willing to work evenings, weekends and holidays, as required.

Travel: As required.

Equal Employment Opportunity Statement The Canadian Football League is an equal opportunity employer, and we are working to create a more diverse and inclusive work environment. We welcome applications from traditionally underrepresented groups such as women, visible minorities, Indigenous peoples, people living with disabilities, and people identifying as LGBTQ2S+.

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