Senior AWS Data Engineer

Apptoza Inc.; Toronto; On-site; CAD 110,000 - 150,000; Full time

Job summary

Apptoza Inc. is seeking a Senior AWS Data Engineer with 12+ years of hands-on experience to design, develop, and support enterprise-scale data platforms on AWS.

The role emphasizes ETL/ELT development, real-time streaming, and production-grade cloud data solutions within a banking environment. You will design scalable data pipelines, optimize processing, and collaborate with cross-functional teams to deliver reliable data solutions using AWS services such as Glue, S3, Lambda, Redshift, DynamoDB,

Qualifications

• 12+ years of experience in Data Engineering.
• Strong hands-on experience with AWS data services (Glue, S3, Lambda, Redshift, DynamoDB).
• Experience building ETL/ELT pipelines and real-time streaming solutions.

Responsibilities

• Design, develop, and maintain scalable data pipelines using AWS services.
• Build and optimize ETL/ELT workflows with AWS Glue (PySpark/Python).
• Develop serverless data processing solutions using AWS Lambda.
• Design and manage data lakes with Amazon S3 and data warehouses with Redshift.
• Work with DynamoDB and other AWS data services for high-performance apps.
• Build real-time streaming with Kinesis and/or Kafka; schedule and monitor with Airflow.
• Implement IaC using CDK or Terraform and monitor production pipelines.

Skills

AWS data engineering

SQL

Python

ETL/ELT

Data pipelines

Kinesis / Kafka

Airflow

IaC (CDK/Terraform)

DynamoDB

Redshift

S3

Tools

AWS Glue

PySpark

Airflow

Terraform

AWS CDK

Kafka

S3

Redshift

DynamoDB

Job description

Duration: 12-Month Contract (Extension Possible)

Job Summary

AWS, SQL, OLAP, OLTP, ETL , PYTHON

We are seeking a Senior AWS Data Engineer with 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

• 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
• 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.