Technology Solutions - Data Platform & Engineering Fall 2026 Co-Op/Intern - $22.5 An Hour
Posted
Economical Technology Solutions - Data Platform & Engineering Fall 2026 Co-Op/Intern - $22.5 An Hour
Summary
A 4-month Fall 2026 co-op/internship on Economical Insurance's data platform team, supporting data ingestion, transformation, and SQL-based analysis in Google Cloud. Day-to-day involves coding in Python, Spark, or Scala, shell scripting, and using tools like Jira, Bitbucket, Jenkins, and Confluence.
Technology Solutions - Data Platform & Engineering Fall 2026 Co-op/InternToronto, ONT, Canada
Work term: Fall 2026
Work term length: 4 months
We are looking for Technology Solutions Co‑op. Through this work, you will utilize system analysis and technical skills. You will gain exposure to Data Engineering practices, distributed computing systems, and business data flows. This position reports to the Big Data Team Lead and receives day‑to‑day supervision from the Project Manager and/or Technical Lead/Specialist.
What you’ll be doing
Understanding Data Engineering concepts and related tools/technologies
Preparing data samples, performing data ingestion and transforming data in Google Cloud
Working with file formats (AVRO, ORC, Parquet) and moving data in and out of cloud‑based DBs
Coding in Python, Spark, or Scala
Writing shell scripts
Preparing and executing SQL‑based queries
Documenting processes using Confluence
Gaining experience with issue tracking (Jira), source code management (Bitbucket), continuous integrations and build tools (Jenkins), package management and testing frameworks
What you bring
Full‑time co‑op program enrollment in Computer Science, Computer Engineering, or a related field
Foundational knowledge of data engineering concepts and interest in working with large‑scale data systems
Experience with programming languages such as Python, Spark, or Scala
Basic understanding of SQL and experience with relational or cloud‑based databases
Exposure to cloud platforms (e.G., Google Cloud) or strong willingness to learn
Familiarity with data formats (AVRO, ORC, Parquet) and scripting/automation (Shell) is an asset
Strong analytical, problem‑solving, and learning agility in a fast‑paced environment
Effective communication and documentation skills
Exposure to tools such as Jira, Bitbucket, Jenkins, or Confluence is an asset, with a collaborative team mindset
Benefits
Meaningful work that supports clients and communities during challenging times
Culture of accountability, empowerment, and collaboration
Opportunities for personal and professional growth and learning through real‑life experience and programs such as Leadership Essentials
Access to employee groups focused on women’s empowerment, LGBTQ+, anti‑racism, cultural equity, and environmental activism
Commitment to positive environmental, social, and governance practices
The hourly compensation for the role starts at $22.50 per hour and will increase based on factors including skills, education, experience, and institutional rates.
Our inclusive work environment welcomes diversity and supports accessibility. If you require accommodation at any time during the recruitment process, please let us know by contacting accessibility@economical.com.
Background checks
This role requires successful clearance of a background check (including criminal checks and leadership references).
Work term: Fall 2026
Work term length: 4 months
We are looking for Technology Solutions Co‑op. Through this work, you will utilize system analysis and technical skills. You will gain exposure to Data Engineering practices, distributed computing systems, and business data flows. This position reports to the Big Data Team Lead and receives day‑to‑day supervision from the Project Manager and/or Technical Lead/Specialist.
What you’ll be doing
Understanding Data Engineering concepts and related tools/technologies
Preparing data samples, performing data ingestion and transforming data in Google Cloud
Working with file formats (AVRO, ORC, Parquet) and moving data in and out of cloud‑based DBs
Coding in Python, Spark, or Scala
Writing shell scripts
Preparing and executing SQL‑based queries
Documenting processes using Confluence
Gaining experience with issue tracking (Jira), source code management (Bitbucket), continuous integrations and build tools (Jenkins), package management and testing frameworks
What you bring
Full‑time co‑op program enrollment in Computer Science, Computer Engineering, or a related field
Foundational knowledge of data engineering concepts and interest in working with large‑scale data systems
Experience with programming languages such as Python, Spark, or Scala
Basic understanding of SQL and experience with relational or cloud‑based databases
Exposure to cloud platforms (e.G., Google Cloud) or strong willingness to learn
Familiarity with data formats (AVRO, ORC, Parquet) and scripting/automation (Shell) is an asset
Strong analytical, problem‑solving, and learning agility in a fast‑paced environment
Effective communication and documentation skills
Exposure to tools such as Jira, Bitbucket, Jenkins, or Confluence is an asset, with a collaborative team mindset
Benefits
Meaningful work that supports clients and communities during challenging times
Culture of accountability, empowerment, and collaboration
Opportunities for personal and professional growth and learning through real‑life experience and programs such as Leadership Essentials
Access to employee groups focused on women’s empowerment, LGBTQ+, anti‑racism, cultural equity, and environmental activism
Commitment to positive environmental, social, and governance practices
The hourly compensation for the role starts at $22.50 per hour and will increase based on factors including skills, education, experience, and institutional rates.
Our inclusive work environment welcomes diversity and supports accessibility. If you require accommodation at any time during the recruitment process, please let us know by contacting accessibility@economical.com.
Background checks
This role requires successful clearance of a background check (including criminal checks and leadership references).