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A leading market research firm in Canada is looking for a Data Engineer to enhance and scale data products, ensuring data quality and driving business impact. Candidates should have over 3 years of data engineering experience, proficiency in Python and SQL, and familiarity with orchestration tools. The role includes mentorship opportunities and offers a collaborative company culture with competitive compensation and career growth support.
We’re reinventing the market research industry. Let’s reinvent it together.
At Numerator, we believe tomorrow’s success starts with today’s market intelligence. We empower the world’s leading brands and retailers with unmatched insights into consumer behavior and the influencers that drive it.
Numerator is a data and technology company reinventing market research. Headquartered in Chicago, IL, Numerator has 1,600 employees worldwide. The company blends proprietary data with advanced technology to create unique insights for the market research industry, which has been slow to change. The majority of Fortune 100 companies are Numerator clients.
Collaborate with cross-functional teams to design, enhance, and scale data products that power analytics and customer-facing solutions.
Lead complex, end-to-end projects focused on improving data quality, integrating advanced statistical and machine learning models, and driving measurable business impact.
Architect and develop pipelines that enforce robust data validation, quality checks, and efficient workflows for model deployment.
Partner with data scientists to streamline model integration, ensuring reliability and performance in production systems.
Mentor junior engineers and contribute to best practices, design standards, and engineering excellence across the team.
3+ years of experience in data engineering, including designing and maintaining data warehouses, building data pipelines, and implementing large-scale data solutions.
Proficiency in Python and SQL, with demonstrated expertise in building efficient, high-quality data transformations.
Strong background in data modeling, ETL design, and orchestration tools (especially Airflow), ensuring business goals are met with data integrity and scalability.
Proven experience deploying cloud-based production solutions in AWS, Azure, or GCP, with emphasis on data reliability across environments.
Familiarity with Machine Learning/Statistical Model Development processes and their data dependencies.
Strong problem-solving ability, intellectual curiosity, and attention to detail, with a focus on delivering high-impact solutions in a fast-paced, collaborative environment.
Deep experience with Amazon Web Services (EC2, RDS, ECS, S3, Lambda, etc.).
Expertise in Terraform, Ansible, or similar IaC tools for infrastructure automation.
Proficiency in Airflow, including DAG design, monitoring, and custom operator development.
Hands-on experience with modern data platforms such as Snowflake, Databricks, or Redshift.
Comfort working with containerized services (Docker, Kubernetes) in production environments.
Background in retail, consumer insights, or marketing data is a strong plus.
Ability to contribute to technical strategy and mentor more junior team members.
An inclusive and collaborative company culture - we work in an open, transparent environment to get things done and adapt to the changing needs as they come
An opportunity to have an impact in a technologically data-driven company that’s changing the market research industry and getting rave reviews
Market-competitive total compensation package
Volunteer time off and charitable donation matching
Strong support for career growth, including mentorship programs, leadership training, access to conferences and employee resources groups
Regular hackathons to build your own projects and Engineering and Data Science Lunch and Learns