AWS Data Engineer with Strong SQL, ETL, Python

Apptoza Inc.; Toronto; Hybrid; CAD 120,000 - 150,000; Full time

Job summary

Apptoza Inc. in Toronto is seeking an AWS Data Engineer with strong SQL, ETL, and Python skills for a 1-year contract hybrid role. You will design, build, and optimize scalable data pipelines on AWS to support analytics and reporting.

The ideal candidate has 10+ years of experience, deep expertise in SQL with stored procedures, and hands-on work with Glue, Redshift, S3, Lambda, Kafka, Airflow, and Step Functions. You will collaborate with data teams, ensure data quality, and enforce governance.

Qualifications

• Expert SQL performance tuning and stored procedures.
• Experience building ETL/ELT pipelines on AWS.
• Strong Python and PySpark for data transformation.
• Hands-on with AWS data services (Glue, Redshift, S3, Lambda).
• Knowledge of Airflow, Kafka, and Step Functions.
• Data governance and security best practices.
• Data modeling and orchestration experience.
• Git and CI/CD for data workflows.

Responsibilities

• Design, build, and optimize scalable data pipelines and systems.
• Develop and optimize complex SQL queries and stored procedures.
• Build and maintain ETL/ELT pipelines on AWS (Glue, Lambda, S3, Redshift).
• Implement data integration from diverse sources into a lake/warehouse.
• Collaborate with analysts and data scientists to meet data needs.
• Monitor pipelines for accuracy, timeliness, reliability.
• Enforce data governance and security in development.

Skills

SQL

Python

PySpark

ETL

AWS

AWS Glue

Redshift

S3

Kafka

Airflow

Lambda

Step Functions

Data modeling

CI/CD for data

Git

Tools

Git version control

Airflow

Job description

AWS Data Engineer with Strong SQL, ETL, Python

Location: Toronto, On

Hybrid (3 days from Office)

Duration : 1yr contract - Extension

Job Summary:

Experience: 10+

Managing cloud infrastructure, Automation and DevOps, Security & Compliance, and Monitoring/Troubleshooting.

We are seeking a highly skilled Data Engineer with deep expertise in SQL (including stored procedures) and AWS-based data engineering solutions.

You will be responsible for designing, building, and optimizing scalable data pipelines and systems that enable analytics, reporting, and data-driven decision-making across the organization.

Key Responsibilities Develop and optimize complex SQL queries and stored procedures for high-performance data processing and transformation.

Build and maintain scalable ETL/ELT pipelines on AWS using services such as Glue, Lambda, S3, Athena, Redshift, Kafka, Airflow, and Step Functions.

Implement and maintain data integration solutions from various data sources into a centralized data lake or data warehouse.

Collaborate with data analysts, data scientists, and business stakeholders to understand data requirements and deliver reliable solutions.

Monitor and troubleshoot data pipelines to ensure data accuracy, timeliness, and reliability.

Apply data governance and security best practices in all development work.

Skills Required Expert-level proficiency in SQL, including performance tuning, writing complex joins, and stored procedures in databases.

Experience with AWS Data Engineering tools

AWS Glue

Amazon Redshift

AWS Lambda

Amazon S3

Kafka

Step Functions

Experience with data modeling, ETL orchestration, and data pipeline development in AWS.

Familiarity with version control systems (e.g., Git) and CI/CD for data workflows.

Airflow

Experience with Python and PySpark. ETL, Python