Role: AWS Data Engineer
Location: Toronto, ON – Hybrid
Contract Role
Job Summary
Key Responsibilities
- Design and develop scalable data pipelines and ETL/ELT processes using AWS services.
- Develop complex and optimized SQL queries for data extraction, transformation, and analysis.
- Build and maintain data solutions using AWS Glue, S3, Lambda, Athena, Redshift, and EMR.
- Develop data transformation workflows using Python/PySpark.
- Perform data integration from multiple sources into AWS data platforms.
- Implement data quality, validation, transformation, and reconciliation processes.
- Optimize data pipelines and SQL queries for performance and cost efficiency.
- Work with business and analytics teams to understand data requirements.
- Troubleshoot data pipeline failures and resolve data-related issues.
- Implement automated testing and monitoring for data pipelines.
- Follow data governance, security, and compliance best practices.
Required Skills
- 8+ years of strong Data Engineering experience.
- Strong hands-on experience with AWS Cloud data services.
- Excellent SQL skills, including complex queries, joins, CTEs, window functions, and query optimization.
- Strong experience with AWS Glue and Amazon S3.
- Experience with Amazon Redshift and/or Athena.
- Strong Python and/or PySpark experience.
- Experience developing ETL/ELT pipelines.
- Experience with data warehousing and data modeling.
- Strong understanding of batch and real-time data processing.
- Experience with Git and CI/CD for data engineering projects.
Preferred Skills
- AWS Lambda
- Amazon EMR
- AWS Step Functions
- Amazon Kinesis
- Apache Spark
- Kafka
- Airflow
- Data Lake / Data Warehouse architecture
- AWS Lake Formation / Glue Data Catalog
Data quality and governance tools
