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Senior AWS Data Engineer - 10+yrs

  • Toronto, ON, Canada

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Job details

Job type
Contract
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Experience
10-12+ years of experience in Data Engineering.
Posting language
English
Posted

Original job description

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.
More about this job

Responsibilities

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.

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.

Skills

  • AWS Glue
  • PySpark
  • Python
  • Amazon S3
  • AWS Lambda
  • Amazon Redshift
  • Amazon DynamoDB
  • Amazon Kinesis
  • Apache Kafka
  • Apache Airflow
  • SQL
  • ETL/ELT
  • Infrastructure as Code
  • AWS CDK
  • Terraform
  • Data Engineering

Visa sponsorship

Not detected in the job text

Categories

  • Data & Analytics
  • Technology
  • Software
  • Finance & Accounting

Keywords

  • AWS
  • AWS Glue
  • PySpark
  • Python
  • Amazon S3
  • AWS Lambda
  • Amazon Redshift
  • Amazon DynamoDB
  • Amazon Kinesis
  • Apache Kafka
  • Apache Airflow
  • SQL
  • ETL/ELT
  • Data Engineering
  • Data Lakes
  • Data Warehousing
  • Real-Time Streaming
  • OLTP
  • OLAP
  • Infrastructure as Code
  • AWS CDK
  • Terraform
  • Production Data Platforms
  • Banking
  • Financial Services
  • CI/CD
  • DevOps
  • Data Governance
  • Agile
  • Cloud Data Solutions

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