AWS Data Engineer

Mississauga, Ontario, Canada
Remote
Posted Oct 23, 2026
1 position

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Employment type: Contract
Experience level: Senior · 5+ years
Posting language: English
Working hours: 40 hours per week
Seniority: Mid-Senior level
Application method: Direct apply is available

Job summary

Design and build scalable AWS data lake solutions and batch and real-time ETL/ELT pipelines, using AWS services to ingest, transform, and prepare enterprise data for analytics. Optimize pipeline performance and cost, implement data quality, governance, and monitoring controls, automate deployments, and collaborate with stakeholders on integration requirements.

Job details

Job Title: AWS Data Engineer Location: Mississauga(Remote) Mode: Contract Responsibilities: Designed and developed scalable AWS Data Lake solutions for ingesting, processing, and analyzing enterprise data. Built and maintained ETL/ELT pipelines using AWS Glue, PySpark, and AWS Lambda. Developed batch and real time data pipelines integrating multiple source systems into Amazon S3 data lakes. Implemented data transformation, cleansing, and enrichment processes using AWS Glue Jobs and Glue Workflows. Managed metadata catalogs using AWS Glue Data Catalog and optimized data discovery capabilities. Designed data ingestion frameworks leveraging S3, Lambda, EventBridge, and Step Functions. Created analytical datasets for reporting and business intelligence consumption. Optimized Glue jobs for performance, scalability, and cost efficiency. Implemented data quality, governance, and monitoring controls across pipelines. Worked with Redshift, Athena, and Lake Formation to support data analytics and governance initiatives. Developed CI/CD processes for data pipelines and automated deployment across environments. Collaborated with business stakeholders, application teams, and data architects to define data integration requirements. Required Skills: AWS Glue AWS Data Lake Amazon S3 PySpark, Python Athena, Redshift Lambda, Step Functions SQL & Data Modeling ETL/ELT Development Lake Formation Data Governance & Data Quality Event Bridge and Data Pipeline Automation

What you’ll do

Requirements

The role requires experience with AWS Glue, data lakes, Amazon S3, PySpark, Python, Athena, Redshift, Lambda, Step Functions, SQL, and data modeling. It also calls for ETL/ELT development, Lake Formation, data governance and quality, and EventBridge-based pipeline automation.