Senior AWS Data Engineer - 10+yrs

Toronto, ON
Hybrid
Posted Oct 7, 2026
1 position

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Employment type: Contract
Experience level: Lead · 12+ years
Apply by: Nov 4, 2026
Posting language: English
Working hours: 40 hours per week
Office presence: 3 days per week
Seniority: Mid-Senior level
Application method: Direct apply is available

Job summary

Design, develop, optimize, and support scalable AWS data pipelines, ETL/ELT workflows, data lakes, warehouses, and real-time streaming solutions. Monitor production systems, implement infrastructure as code, and collaborate with cross-functional teams using Agile practices.

Job details

Role: Senior AWS Data Engineer - 10+yrs Location: Toronto, ON Work Model: Hybrid – 3 Days/Week Onsite Duration: 12-Month Contract (Extension Possible) Job Summary We are seeking a Senior AWS Data Engineer with 10- 12+ years of hands-on experience designing, developing, and supporting enterprise-scale data platforms on AWS. The ideal candidate will be a strong individual contributor with deep expertise in AWS data engineering, ETL development, and real-time data streaming technologies. This role requires someone who can quickly understand business requirements, build scalable data pipelines, optimize data processing, and support production-grade cloud data solutions in a fast-paced banking environment. Key Responsibilities Design, develop, and maintain scalable data pipelines using AWS services. Build and optimize ETL/ELT workflows using AWS Glue (PySpark/Python). Develop serverless data processing solutions using AWS Lambda. Design and manage data lakes using Amazon S3. Develop and optimize data warehouse solutions using Amazon Redshift. Work with Amazon DynamoDB and other AWS data services for high-performance applications. Build and support real-time data streaming solutions using Amazon Kinesis and/or Apache Kafka. Develop, schedule, and monitor workflows using Apache Airflow. Write complex SQL queries and optimize database performance across OLTP and OLAP systems. Implement Infrastructure as Code (IaC) using AWS CDK or Terraform. Monitor, troubleshoot, and support production data pipelines. Collaborate with cross-functional teams to deliver reliable and scalable data solutions. Follow Agile development practices and participate in sprint planning, code reviews, and technical discussions. Required Skills 10-12+ years of experience in Data Engineering. Strong hands-on experience with: AWS Glue (PySpark/Python) Amazon S3 AWS Lambda Amazon Redshift Amazon DynamoDB Amazon Kinesis and/or Apache Kafka Apache Airflow SQL Python Strong understanding of ETL/ELT development. Experience working with OLTP and OLAP databases. Hands-on experience with Infrastructure as Code (AWS CDK or Terraform). Experience building and supporting production-grade AWS data platforms. Strong analytical, troubleshooting, and problem-solving skills. Excellent communication and collaboration skills. Preferred Qualifications Experience in the Banking or Financial Services domain. Experience with real-time event-driven data architectures. Familiarity with CI/CD pipelines and DevOps practices. Knowledge of data governance, security, and AWS best practices. AWS Certifications are an asset. Ideal Candidate Strong hands-on AWS Data Engineer with proven technical expertise. Individual contributor capable of designing and developing scalable cloud data solutions. Experience delivering enterprise-grade AWS data platforms in production environments. Able to work independently while collaborating effectively with cross-functional teams.

What you’ll do

Requirements

Requires 10–12+ years of data engineering experience and strong hands-on expertise with AWS data services, Python, SQL, ETL/ELT, and production-grade cloud data platforms. Candidates should also have experience with OLTP and OLAP databases, infrastructure as code, and strong troubleshooting and collaboration skills; banking experience is preferred.