Data Engineering Intern: Pipelines & Snowflake

Environics Analytics; Toronto; On-site; CAD 40,000 - 60,000; Full time

Job summary

Environics Analytics in Toronto invites a Data Development Intern to help build and modernize data infrastructure powering demographic and behavioral products. You will design automated pipelines in SQL and Python, support migration to Snowflake, and contribute to QC systems ensuring accurate outputs across geographies.

This hands-on role offers real ownership of production code and exposure to large-scale datasets from Statistics Canada and other sources, with collaboration across researchers

Qualifications

• Enrolled in or recently completed a graduate program (Master's) in Computer Science, Data Science, Statistics, Geography, Engineering, or a related quantitative field.
• Undergraduate candidates with strong relevant experience will also be considered.
• Prior experience in data engineering, data analysis, or software development.
• Comfort working with large-scale structured datasets (millions of rows across related tables).

Responsibilities

• Design, build, and maintain automated data pipelines for ETL, modelling, and quality control across demographic data products.
• Help migrate and refactor legacy workflows into SQL (T-SQL) and Python, improving scalability, maintainability, and version control.
• Develop stored procedures, temp table-based workflows, and batch scripts to support large-scale data transformation.
• Build automated QC checks and validation logic to catch anomalies and inter-vintage inconsistencies early in the pipeline.
• Collaborate with data developers, Research Associates, and Technical Leads to translate data product methodology into reliable, repeatable code.
• Present design approaches before building, validate results after, and participate in code reviews.
• Use Azure DevOps and Git for version control and work item tracking; maintain documentation on SharePoint.
• Investigate and prototype new tools, libraries, or pipeline architectures, including Snowflake-native approaches, that improve team efficiency or product quality.
• Use AI coding tools (e.g., GitHub Copilot) as a core part of daily development to accelerate scripting, refactoring, and code review.
• Apply AI-assisted approaches to documentation and QC, such as generating test cases, drafting validation logic, or summarizing pipeline behaviour.
• Critically evaluate AI-generated code and output, verifying correctness and understanding the underlying SQL/Python well enough to own what ships.

Skills

SQL

Python

pandas

VS Code

Jupyter Notebook

SQL Server Management Studio

Git

Azure DevOps

GitHub Copilot

Education

Master's degree in Computer Science, Data Science, Statistics, Geography, Engineering

Undergraduate candidates with strong relevant experience

Tools

Snowflake

Airflow

Dask

ETL tools

APIs

Job description

Environics Analytics in Toronto invites a Data Development Intern to help build and modernize data infrastructure powering demographic and behavioral products. You will design automated pipelines in SQL and Python, support migration to Snowflake, and contribute to QC systems ensuring accurate outputs across geographies.

This hands-on role offers real ownership of production code and exposure to large-scale datasets from Statistics Canada and other sources, with collaboration across researchers