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AWS Data Engineer – ETL, Python & SQL

Summary

Builds and maintains cloud-based data pipelines (ETL) using Python, SQL, and AWS tools to process large datasets, ensuring data quality and enabling analytics. Focuses on automation, deployment, and monitoring in hybrid cloud environments.

Hybrid (2 days per week in-person at Toronto office preferred)

Skills: Digital : Amazon Web Service (AWS)

Cloud Computing

AWS Data Engineer - ETL, Python & SQL

Toronto, ON

Digital : Python for Data Science

Digital : Google Data Engineering

Experience Required: 6-8 Years

Required Skills and Experience

  • Must have working knowledge in designing and implementing data pipelines on any of the cloud providers (AWS is preferred). Must be able to work with large volumes of data coming from various sources. Perform data cleansing, data validation etc.
  • Hands on ETL developer who is good at python, SQL. AWS services like glue, glue crawlers, lambda, red shift, Athena, s3, EC2, IAM, Monitoring and Logging mechanisms- AWS CloudWatch, setting up alerts.
  • Deployment knowledge on cloud. Integrate CI/CD pipeline to build artifacts and deploy changed to higher Environments.
  • Scheduling frame works Airflow, AWS Step functions 5. Excellent Communication skills, should be able to work collaboratively with other teams

See also

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