AWS Data Engineer

Toronto, ON
Hybrid
Posted Oct 7, 2026
1 position

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Employment type: Contract
Experience level: Senior · 8+ years
Apply by: Nov 4, 2026
Posting language: English
Working hours: 40 hours per week
Seniority: Mid-Senior level
Application method: Direct apply is available

Job summary

Develop and support scalable AWS data pipelines and cloud data platforms, using services such as Glue, S3, Lambda, Step Functions, Redshift, Athena, and EMR. Transform, validate, and reconcile data; maintain data quality; optimize pipelines; troubleshoot production issues; automate deployments; and follow banking security, compliance, and governance standards.

Job details

AWS Data Engineer – Banking / Financial Services Location: Toronto, ON Hybrid Contract: Long Term | Experience: 8+ Years Job Summary Seeking an experienced AWS Data Engineer to build and support scalable data pipelines and cloud data platforms for banking and financial services applications. Key Responsibilities Develop ETL/ELT pipelines using AWS Glue, S3, Lambda, Step Functions. Build data processing solutions using Python, PySpark, and SQL. Work with Redshift, Athena, and EMR for data storage and analytics. Perform data transformation, validation, reconciliation, and quality checks. Optimize data pipelines and troubleshoot production issues. Implement CI/CD and infrastructure automation using Git, Jenkins, Terraform/CloudFormation. Collaborate with data architects, developers, and business teams. Follow banking security, compliance, and data governance standards. Must-Have Skills AWS | S3 | Glue | Redshift | Athena | EMR | Lambda | Python | PySpark | SQL | ETL/ELT | Data Warehousing | Git | CI/CD Preferred Banking / Payments / Financial Services experience. Kafka/Kinesis, Snowflake, Databricks, Airflow/MWAA, Terraform. Experience with financial, customer, transaction, or regulatory data.

What you’ll do

Requirements

The role requires 8+ years of experience and hands-on skills in AWS, Python, PySpark, SQL, ETL/ELT, data warehousing, and CI/CD. Banking, payments, or financial services experience is preferred, as is familiarity with Kafka or Kinesis, Snowflake, Databricks, Airflow or MWAA, and Terraform.