Sr. AWS Data Engineer, Infrastructure With Strong SQL

Toronto, Ontario, CanadaHybridFull TimeSeniorPosted 2 months ago

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Role summary

Seeking a Sr. AWS Data Engineer with strong SQL and AWS expertise for a 1-year hybrid contract in Toronto. The role focuses on managing cloud infrastructure, automation, DevOps, security, and monitoring. Responsibilities include designing, building, and optimizing scalable data pipelines and systems using AWS services like Glue, Lambda, S3, Athena, Redshift, Kafka, and Step Functions. Key tasks involve developing complex SQL queries and stored procedures, implementing data integration solutions, and ensuring data accuracy and reliability. Familiarity with version control and CI/CD for data workflows is also required.

Client JD

Role: Sr. AWS Data Engineer, Infrastructure With Strong SQL
Location: Toronto
Client: Banking Labs/BMO
1yr contract
Hybrid

Job Summary:
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
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

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