Data Engineer

GFL Environmental Inc.•Vaughan, ON

30d•Onsite

About The Position

GFL is expanding and is looking for a Data Engineer in Vaughan, ON, to bring fresh ideas and grow with a dynamic team. GFL is a leading diversified environmental services company in North America, offering comprehensive solid waste management services across Canada and 18 U.S. states. Known for its signature green trucks and equipment, GFL provides a wide range of environmental and industrial services, consolidating sophisticated approaches to meet customer needs. The company emphasizes safe, accessible, and cost-effective solutions to promote environmental responsibility, embodying the 'Green For Life' philosophy.

Requirements

Proficient in AWS services relevant to data engineering, such as Amazon S3, Amazon Redshift, AWS Glue, Amazon EMR, and AWS Lambda.
Strong programming skills in languages such as Python, SQL, and Java.
Experience in data modeling, ETL (Extract, Transform, Load) development, and understanding of data warehousing concepts.
Knowledge of database management, performance tuning, and query optimization.
Strong analytical and problem-solving abilities, with the capacity to work on complex data systems.
Excellent communication and teamwork skills, with the ability to work effectively in a collaborative environment.
A bachelor’s degree in computer science, Engineering, or a related field.
Previous experience as a data engineer or in a similar role, specifically with AWS cloud services.
Valid work authorization in the country where the job is located is required.

Nice To Haves

AWS Certified Data Analytics - Specialty.
AWS Certified Solutions Architect - Associate or Professional.

Responsibilities

Design and Implementation of Data Pipelines: Develop and maintain robust, scalable, and efficient data pipelines that can ingest, process, and distribute data across multiple AWS services and systems.
Data Storage and Database Management: Design and implement data storage solutions using AWS data services such as Amazon RDS, Amazon DynamoDB, Amazon Redshift, and Amazon S3, ensuring data integrity, availability, and security.
Data Processing and Analysis: Utilize AWS analytics and data processing services such as AWS Glue, Amazon EMR, and AWS Lambda to analyze data, derive insights, and support business decision-making.
Data Security and Compliance: Implement and manage security measures to protect data and ensure compliance with data protection regulations and AWS best practices, including encryption, access controls, and audit logging.
Optimization and Scalability: Monitor, optimize, and scale data infrastructure and applications to improve performance, reduce costs, and accommodate growing data volumes.
Collaboration and Support: Work closely with data scientists, business analysts, and other stakeholders to understand data requirements and deliver solutions that meet business needs. Provide support for data-related technical issues.
Innovation and Continuous Improvement: Stay abreast of new AWS features and technologies and explore innovative ways to enhance data architecture and operations for better efficiency and effectiveness.