Role: AWS Data Engineer With Solid SQL
Location: Toronto, Hybrid
Experience Level: 8-12 yrs

Job Summary

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

- 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

📌 AWS Data Engineer with Strong SQL, GLUE, Lambda,PySpark, Kafka (Canada)
🏢 Atlantis IT Group
📍 Canada