AWS Data Engineer with Strong SQL, GLUE, Lambda, S3, PySpark, Kafka

Role: AWS Data Engineer with Strong SQL, GLUE, Lambda, S3, PySpark, Kafka

Location: Toronto

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.

• 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.
• 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

Athena

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