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Greater Toronto Area, Canada Randstad Digital Full timeRole SummaryWe are seeking a highly skilled and motivated Data Engineer to join our team. This role is central to designing, building, and maintaining the systems and infrastructure for data storage, processing, and analysis. You will work within a multidisciplinary Agile team to deliver high-quality data products, support complex AI/ML initiatives, and...
Data Engineer
1 month ago
We’re seeking a seasoned Data Engineer who can design and deliver modern, cloud-based data solutions that enable advanced analytics and reporting. You’ll be part of a collaborative engineering team responsible for building reliable data infrastructure and pipelines to support business growth and innovation. Duration: 6mo Location: Toronto (onsite) Rate: open Workhours/week: 40 Your Technical Toolkit Languages: Python, SQL Data Platforms: Snowflake (mandatory), AWS (or other cloud) Tools: Airflow, Git, CI/CD frameworks Expertise: Data modeling, warehousing, performance optimization, ETL/ELT architecture What You Bring 8-10 years of overall experience in data engineering in development environment Strong, practical expertise in Python, SQL, Snowflake, Airflow, and data warehouse development. 2-3 years of experience working with AWS or another cloud platform. A proven background in designing and deploying end-to-end data pipelines in cloud environments. Hands-on understanding of CI/CD tools and automated deployment processes. Prior experience working in a development-focused environment (not production support). Excellent communication skills and the ability to collaborate effectively across engineering and business teams. What You’ll Do Design and build data pipelines that process and integrate large datasets from multiple sources. Develop and maintain ETL/ELT workflows using Python and SQL for data cleansing, validation, and transformation. Manage data warehousing in Snowflake, ensuring performance, scalability, and reliability. Use Airflow for workflow automation, scheduling, and monitoring. Deploy and scale solutions in AWS (preferred) or another major cloud platform. Implement CI/CD pipelines to automate testing, deployment, and delivery. Collaborate with cross-functional teams to design and optimize data models and workflows.
