Top Data Engineer Jobs in Toronto

The role involves designing, developing, and optimizing big data solutions using PySpark, mentoring junior engineers, and leveraging AI tools to enhance development productivity.

Own Venn's data infrastructure, build reliable data pipelines, design trusted data models, and improve data quality across the organization to support business decisions.

Lead and influence teams in data engineering projects, focusing on data infrastructure, analytics, performance, and security while mentoring and providing technical guidance.

Lead Full Stack Data Engineer responsible for architecting, developing, and optimizing data solutions, mentoring teams, and driving AI integration in data processes.

The Full Stack Data Engineer will design and implement scalable data solutions, optimize data pipelines, and leverage AI tools to enhance productivity. Collaboration with teams and engagement with data stakeholders is key.

Build and optimize Databricks-based data pipelines and Delta Lake solutions, capture and process data quality metrics, and create Power BI dashboards for data governance and operational monitoring. Partner with stakeholders to define requirements, implement scalable data models, troubleshoot performance, and promote data engineering best practices, testing, and deployment.

Design, build, and operate scalable ETL/ELT pipelines and data storage for B2B products. Ensure data quality, low-latency performance, CI/CD, testing, monitoring, and technical leadership across cloud-based analytics systems.

As a Data Engineer, you will build and maintain data systems for drug safety AI tools, ensuring reliable data processing and storage for research teams.

Design and maintain data pipeline architecture, manage AWS services, optimize data systems, and ensure efficient ETL operations across various data sources.

The Principal Data Engineer at RAVL will design and implement enterprise-grade data and AI platforms, mentor engineers, and influence architectural standards across teams.

As a Data Engineer, you'll design, build, and maintain data pipelines, ensure data quality, and collaborate with stakeholders to deliver data solutions.

The Senior Pyspark Data Engineer will manage large-scale data processing systems, conduct feasibility studies, provide user support, and develop security measures while acting as a subject matter expert in applications development.

Responsible for systems analysis, programming, and managing application development projects. It involves data processing management and consulting with users. Must ensure compliance with regulations while supporting business units and mentoring junior staff.

Lead design, development, testing, implementation, and support of scalable ETL/data integration solutions. Provide technical direction for Talend-based ETL, SQL optimization, mainframe-to-distributed replication, data validation/reconciliation, performance tuning, and production support. Coordinate deliverables, run design/code reviews, partner with cross-functional teams, and drive process and framework improvement to increase reliability, maintainability, and scalability of enterprise data services.

Design and optimize scalable data pipelines, develop reusable frameworks, troubleshoot production issues, and enforce data engineering standards while collaborating with stakeholders.

The role involves leading application systems analysis, programming, and managing development teams to implement new systems in coordination with the technology team, while ensuring compliance and best practices.

Develop and extend data ingestion pipelines for AI model training, manage cloud infrastructure, and collaborate with AI scientists. Bring new audio data sources into the system.

Responsible for designing and operating data architecture, building ETL/ELT pipelines, implementing data quality frameworks, and collaborating on ML initiatives.

The Senior Data Engineer will design and maintain scalable data pipelines, collaborate with stakeholders, and ensure data governance and quality. Responsibilities include project ownership, mentoring juniors, and implementing data solutions across platforms.

The Big Data Engineer will design and maintain data pipelines, manage AWS infrastructure, optimize ETL processes, and support operational activities while mentoring junior staff.

The Senior Data Engineer will design and maintain data pipelines, optimize data warehouses, integrate diverse data sources, and enforce data quality SLAs while mentoring junior engineers and participating in architectural planning.

The Data Engineer will design and manage data pipelines and architectures, ensuring data quality and security while collaborating with cross-functional teams for effective analytics and reporting.

As a Software Engineer, you will create tools and pipelines for AI development, manage data solutions for ML teams, and ensure high-quality code.

Design and build scalable ETL data pipelines and RESTful APIs/microservices. Improve performance, monitor and troubleshoot data flows, ensure data security/compliance, write tests, and collaborate cross-functionally.

Design and build reusable, metadata-driven data and AI engineering frameworks using Databricks and cloud-native services. Architect and deploy Delta Live Tables, Lakeflow, and orchestrated Databricks workflows for automated data processing and AI agent deployment. Implement RAG/Graph RAG solutions and agent orchestration (AgentOps, Agent-bricks, LangGraph), integrate real-time streams, manage AI agent lifecycles, and ensure governance via Unity Catalog or AWS Glue.