AWS Data Engineer

Virtusa; Toronto; On-site; CAD 100,000 - 120,000; Full time

Job summary

A technology services company is seeking a highly skilled Data Engineer in Toronto, Ontario, to design and maintain scalable data pipelines on AWS. Candidates should have extensive experience in AWS Glue, Redshift, and Athena, along with a deep understanding of ETL processes. This role requires collaboration with teams to deliver reliable data solutions that support analytics and machine learning initiatives.

Qualifications

• 9 years of experience in data engineering.
• Strong expertise in AWS Glue, Redshift, and Athena.

Responsibilities

• Design, build, and manage high-performance ETL/ELT pipelines.
• Develop and optimize data warehousing solutions.
• Implement efficient query solutions using Athena and Redshift.

Skills

AWS Glue (ETL/PySpark)

Amazon Redshift

Amazon Athena

Data Lake (S3-based)

SQL (T-SQL, Redshift SQL)

ETL Design Data Pipelines

Data Modeling (Star, Snowflake)

AWS Lambda & Step Functions

AWS IAM, CloudWatch, SNS/SQS

Job description

We are seeking a highly skilled and experienced Data Engineer with 9 years of experience to design, develop, and maintain scalable data pipelines and infrastructure on AWS. The ideal candidate will have strong expertise in AWS Glue, Redshift, Athena, and related AWS services. The role demands end-to-end ownership of data workflows, performance optimization, and delivering reliable data solutions to support business intelligence, analytics, and machine learning initiatives.

Responsibilities

• Design, build, and manage scalable and high-performance ETL/ELT pipelines using AWS Glue, PySpark, and Step Functions.
• Develop and optimize data warehousing solutions using Amazon Redshift for structured and semi-structured data.
• Implement efficient query solutions using Amazon Athena, Redshift Spectrum, and data lake patterns.
• Collaborate with data scientists, analysts, and business teams to understand data requirements and deliver reliable solutions.
• Ensure data quality, integrity, and compliance through robust validation and transformation techniques.
• Implement monitoring, logging, and alerting solutions for data pipeline health using CloudWatch and other AWS-native tools.
• Manage and orchestrate jobs via AWS Glue Workflows, Step Functions, or custom schedulers (e.g., Apache Airflow).
• Tune performance for ETL jobs and SQL queries in Redshift and Athena for faster execution.
• Handle data modeling, schema design, and partitioning strategies for large-scale datasets.
• Stay updated with AWS data services and recommend architecture improvements and cost optimizations.

Skills

• AWS Glue (ETL/PySpark)
• Amazon Redshift
• Amazon Athena
• Data Lake (S3-based)
• SQL (T-SQL, Redshift SQL)
• ETL Design Data Pipelines
• Data Modeling (Star, Snowflake)
• AWS Lambda & Step Functions
• AWS IAM, CloudWatch, SNS/SQS