AWS Data Engineer - SQL, ETL , PYTHON, Infrastructure

Job Title: AWS Data Engineer - SQL, ETL , PYTHON, Infrastructure

Location: Toronto, ON

Work Model: Hybrid 3 Days/Week Onsite

Duration: 12-Month Contract (Extension Possible)

Job Summary

AWS, SQL, OLAP, OLTP, ETL , PYTHON, Infrastructure

We are seeking a Senior AWS Data Engineer with 10+ 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

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.