Data Engineer

Armstrong Fluid Technology•Toronto, ON

About The Position

Imagine working at the forefront of innovation in fluid-flow technology, with over 1,400 colleagues across the globe, and contributing to a legacy of excellence that spans eight manufacturing facilities on four continents. Armstrong Fluid Technology is more than just a leader in our industry; we are a community of the brightest and most creative minds, driven by a shared mission to engineer the future and safeguard our planet. As part of our team, you'll be immersed in an environment that fosters growth, creativity, and collaboration. Here, you'll have the opportunity to push boundaries, tackle exciting challenges, and develop cutting-edge solutions that promote energy efficiency and reduce environmental impact. Every day offers the chance to make a meaningful contribution to a more sustainable future, driving innovations that help lower global carbon footprints. Together, we’re creating a legacy that goes beyond business—one that’s changing the world for the better. This role involves hands-on work with data from various sources, including SQL servers, APIs, and more. The ideal candidate will be responsible for cleaning and transforming data, creating rich PowerBI reports, developing data warehouses, and performing ETL operations. Familiarity with Python and AWS services related to data management is essential, while knowledge of C# and .NET is a plus.

Requirements

Bachelor’s degree in computer science, Information Technology, Data Science, or a related field.
Minimum of 3-5 years of experience in data engineering, data analysis, or a similar role.
Proficiency in SQL and experience with SQL servers.
Strong knowledge of Python and its data-related libraries (e.g., Pandas, NumPy).
Experience with AWS services such as S3, Redshift, Glue, and EKS.
Extensive experience with PowerBI for report creation, visualization, and data modeling.
Proven experience in designing, developing, and maintaining data warehouses.
Understanding of ETL processes and data warehousing concepts.
Familiarity with containers and Kubernetes.

Nice To Haves

Knowledge of C# and .NET is a plus.

Responsibilities

Extract, transform, and load (ETL) data from multiple sources such as SQL servers, APIs, and other data repositories.
Clean and preprocess data to ensure accuracy and reliability.
Design, develop, and maintain data warehouses to support business intelligence and analytics.
Optimize data warehouse performance and ensure data integrity and security.
Design and create comprehensive PowerBI reports and dashboards to visualize data insights and support decision-making processes.
Implement advanced PowerBI features such as DAX calculations, custom visuals, and data modeling to enhance report functionality.
Collaborate with cross-functional teams to understand data requirements and deliver solutions.
Utilize Python for data manipulation and automation tasks.
Leverage AWS services for data storage, processing, and management.
Implement best practices for data governance and security.
Perform data analytics to identify trends, patterns, and insights that drive business strategies and improvements.
Utilize containers and Kubernetes for deploying and managing data solutions.