Data Engineer at Environics Analytics in Toronto, Ontario, CA

ROLE OBJECTIVE

Reporting to the Manager, Data Development, the Data Engineer plays a central role in building, maintaining, and modernizing the data infrastructure that powers Environics Analytics' core demographic and behavioural data products. The Data Development team works across a wide range of data sources (including Statistics Canada, IRCC, CRA, and third-party survey data) applying rigorous ETL, quality control, and modeling pipelines to produce market-ready outputs at national to small area geographies.

The Data Engineer will design and implement robust, automated data pipelines in SQL and Python, refactor and migrate legacy workflows, and contribute to modern quality control systems that ensure the accuracy and consistency of our data products across vintages. While the role is primarily data engineering, it also involves elements of data analysis and quality control, with opportunities to engage directly with the methodology and source data underpinning EA's product suite.

SPECIFIC RESPONSIBILITIES AND DUTIES

To effectively fulfill the responsibilities of this position, the employee must be able to do the following:

• Design, build, and maintain automated data pipelines for ETL, modeling, and quality control processes across demographic data products.
• Migrate and refactor legacy workflows into SQL (T-SQL) and Python, improving scalability, maintainability, and version control.
• Develop and maintain stored procedures, temp table-based workflows, and batch processing scripts to support large-scale data transformation.
• Implement automated quality control checks and validation logic to catch anomalies, constraint violations, and inter-vintage inconsistencies early in the pipeline.
• Collaborate with Research Associates and Technical Leads to understand data product methodology and translate it into reliable, repeatable code.
• Engage in planning and alignment with stakeholders by presenting design concepts and proposed approaches prior to execution, validating results upon completion, and participating in code reviews to maintain quality and shared understanding across the team.
• Maintain version control discipline using Azure DevOps and Git; use Azure DevOps for task tracking and work item management. Leverage AI coding tools such as GitHub Copilot to accelerate development and code review workflows.
• Investigate and prototype new tools, libraries, or pipeline architectures that improve team efficiency or data product quality.
• Communicate pipeline statuses, issue diagnoses, and technical findings clearly to both technical and non-technical stakeholders.

QUALIFICATIONS AND REQUIRED SKILLS

Education

University degree in Computer Science, Statistics, Mathematics, Geography, Engineering, or a related quantitative field. Graduate-level studies are an asset but not required.

Experience

• Two or more years of experience in a data engineering, data analysis, or software development role. Graduate studies may count toward this criterion.
• Experience working with large-scale structured datasets (millions of rows across multiple related tables) in a production context.

Technical Skills

• Strong SQL (T-SQL) including complex queries, window functions, stored procedures, and set-based transformation logic.
• Proficiency in Python for data processing and automation, including familiarity with pandas and numpy.
• Experience building and maintaining multi-step ETL pipelines.
• Comfort working in development environments such as VS Code, Jupyter Notebook, and MS SQL Server Management Studio.
• Experience with version control using Git and Azure DevOps; prior use of Azure DevOps for task tracking and work item management.
• Comfort leveraging AI coding tools such as GitHub Copilot to accelerate development and improve code quality.
• Familiarity with geospatial data analysis and Canadian census geographies (e.g., DA, CT, CSD, CMA) is an asset.
• Experience with Snowflake or cloud-based data warehousing is strongly preferred.
• Exposure to Dask or other distributed/parallel computing frameworks in Python is beneficial.
• Experience with workflow scheduling tools such as Apache Airflow or equivalent pipeline orchestration platforms is an advantage.

Additional Technical Skills (at least two preferred)

• Familiarity with statistical concepts relevant to demographic or socioeconomic data (e.g., imputation, aggregation, index construction).
• Experience with Canadian data sources such as Statistics Canada, IRCC, or CRA administrative data.
• Experience working with APIs for data ingestion or product delivery.

Analytical Skills

Aptitude for problem-solving and a desire to continuously improve processes. Comfortable identifying root causes of data anomalies and proposing systematic solutions.

Judgment

Displays willingness to make timely decisions, including appropriate people in the decision-making process. Exhibits sound and accurate judgment; supports and explains reasoning for decisions.

Planning/Organizing

Prioritizes and plans work activities effectively. Able to manage multiple tasks across concurrent product development cycles.

Teamwork

Balances team and individual responsibilities. Exhibits objectivity and openness to others' views, giving and welcoming feedback. Puts success of team above own interests and demonstrates ability to build morale and group commitments to goals and objectives. Supports everyone's efforts to succeed.

Communication Skills

Able to clearly communicate ideas and expectations. Effectively listens for understanding and asks questions for clarification. Presents ideas effectively in both verbal and written form, including documentation and process write-ups.

Interpersonal Skills

Approachable and easy to talk to. Relates well to all kinds of people in the organization. Able to effectively build rapport with others. Uses diplomacy and tact. Maintains composure and shows an ability to resolve conflicts and gain agreement. Comfortable working in a multidisciplinary team of researchers and data professionals.

ABOUT ENVIRONICS ANALYTICS

• Environics Analytics (EA) is a marketing services company that specializes in geodemographic-based segmentation, site evaluation modelling and custom analytics.
• EA is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. If you require any accommodation to participate in the hiring process, please note the request in your application. We welcome people of all abilities.
• At EA, you will solve meaningful and challenging tasks with a friendly team of the most brilliant minds. We hire personality, not just a pair of hands. Here you're free to express your unique qualities, explore different domains and technologies that interest you.