Top Data Engineer Jobs in Toronto

Design and maintain scalable ELT/ETL data pipelines to process large volumes of data, ensuring quality, integrity, and efficiency across platforms.

As a Data Engineer, you will work with a team to maintain database systems, create code and scripts, and ensure data accuracy for various product offerings. You will focus on database development, data transformation processes, and collaborate in an agile environment.

As a Principal Data Engineer at Autodesk, you will be responsible for enhancing data processing and analytics systems, developing ES pipelines, ensuring data quality, and collaborating with various teams. You will lead a team of engineers, make architectural decisions, and focus on modernizing existing systems to scale with business needs.

The Staff Data Engineer will build and maintain large-scale data pipelines, define data models, and establish data quality and governance frameworks, collaborating with business units and engineering teams.

As a Data Engineer at Travelers, you will construct data pipelines, build and deploy data solutions to support AI and ML initiatives, and ensure data quality. Key responsibilities include designing complex data solutions, analyzing data sources, and collaborating with teams to enhance data accessibility and governance.

The Data Engineer/Analyst will automate workflows, package models, and operationalize analytics solutions. Responsibilities include data quality assurance, reporting, and implementing systems to enhance operational efficiency. The role requires working on high-impact business projects, collaborating across teams, and driving data-informed decision-making.

The Data Engineer will gather, curate, and preprocess large datasets, ensuring data quality and integrity. Responsibilities include exploring datasets using statistical techniques and machine learning, communicating findings through visualizations, and proposing enhancements to data processes. Collaboration with various teams is key to delivering impactful data solutions.

As a Senior Finance Data Developer, you will design and implement Data Lake pipelines for integrating data from ERP systems to AWS S3. You will also develop workflows using Apache Airflow, optimize data pipelines, and collaborate with accounting teams to enhance reporting capabilities. Your role includes monitoring and troubleshooting data integrity and performance issues, ensuring the reliability of data systems.

The Data Engineer will design, build, and optimize data pipelines, ensure data governance compliance, support stakeholders in defining data requirements, and manage data in Azure while promoting self-service analytics across the organization.

As a Senior Data Engineer, you will build and maintain a cloud-based data stack, develop analytics products, and ensure data integrity.

As an AWS Data Engineer, you will design, build, and maintain scalable data pipelines using AWS cloud infrastructure. Responsibilities include implementing data transformation workflows, optimizing performance, and collaborating with cross-functional teams on analytics and BI initiatives.

As a Data Engineer at Sporty, you will design and maintain data pipelines, ensure data quality, and work on data applications and architectures for machine learning initiatives.

As a Data Engineer, you will design, build, and maintain data pipelines and ETL processes, ensuring data quality and optimizing workflows for performance.

Responsible for designing and maintaining data pipelines, collaborating with data scientists and analysts, and building analytical models to inform decision-making in People Analytics.

The Data Engineer II will design, build, and optimize systems for metadata processing on a massive scale, collaborating closely with various teams.

As a Data Engineer at Clover, you'll develop data pipelines, tools for analytics and machine learning, and work on data governance and ETL processes. Collaboration with various teams and external parties is essential to ensure data accessibility and improve healthcare outcomes.

The ML Data Engineer will develop and manage robust feature engineering ETL pipelines for machine learning applications. Responsibilities include optimizing low-latency data pipelines, supporting the ML lifecycle, and ensuring compliance and data governance. Close collaboration with data scientists and other teams is essential to align data efforts with business needs.