Design, implement, and maintain data pipelines using AWS Glue, Python, PySpark and other AWS services.
Develop and manage ETL workflows to integrate, transform, and load data from various sources.
Optimize and maintain database systems, including PostgreSQL, and other SQL-based databases.
Collaborate with stakeholders to gather requirements and ensure data solutions meet business needs.
Monitor and troubleshoot data pipelines to ensure reliability and accuracy.
Leverage AWS services, including Athena, to build scalable, efficient, and secure data solutions.

Requirements

Strong experience with AWS Glue for data integration and transformation.
Hands-on expertise with ETL tools and processes in AWS using Python and PySpark.
Solid understanding of relational database systems, particularly PostgreSQL, and SQL.
Proficiency in writing efficient SQL queries and optimizing database performance.
Practical experience in building and managing ETL pipelines in a cloud environment.
Familiarity with other AWS services related to data processing (e.g., S3, Lambda, Athena, etc.)
Any experience with Terraform for IaC, GitLab CI or Docker.

Benefits

Generous Time Off
Above Average Benefits (Dental, Health, Vision, STD, LTD, AD&D, Life, Dependent Life)
Home Office Benefit Program
Yearly Professional Development Budget
Annual Fitness Benefit
Lunch & Learns and Virtual Events
Annual In-Person Celebrations
RRSP with Company Match
Volunteer Days
Sports Tickets for Blue Jays games
Birthday Club

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

AWS GluePythonPySparkETLPostgreSQLSQLSQL queriesTerraformGitLab CIDocker

Soft Skills

collaborationstakeholder engagementtroubleshootingmonitoringproblem-solving