Top Data Engineer Jobs in Toronto

The Principal Engineer, Data Solutions leads technical standards in data modeling and analytics, mentors team members, solves complex data problems, and develops scalable data solutions, focusing on hands-on coding and code quality.

The Full-Stack Developer will design, develop, and maintain integrations, APIs, and applications for MaintainX, focusing on high-quality, reliable code and collaboration with teams.

Lead data engineering strategy and solution design for Snowflake-based platforms. Build and maintain high-performance data pipelines (dbt, SQL, Python), ensure data quality and governance, perform root-cause analysis, lead agile delivery, mentor engineers, collaborate with architects and QA, produce technical documentation, and support hiring and onboarding activities to enable analytics and AI initiatives.

Design, build, and operate scalable metadata harvesting pipelines and connectors across cloud and on-prem platforms. Integrate with Collibra/Data Compass and other catalogs, extract lineage/classification/operational metadata, implement reconciliation, monitoring, security, and CI/CD practices, and mentor engineers to support enterprise data discovery and governance.

Design and build scalable production data pipelines and warehouse models to support AI, analytics, and product teams. Own ingestion, transformation, testing, monitoring, and data quality. Build shared platform capabilities, collaborate cross-functionally, and define practices and cloud architecture for a new regional data engineering team.

The Software Engineer for Data Infrastructure & Acquisition will manage data collection for model training, optimize ingestion pipelines on GCP, and collaborate with the AI team to enhance data quality and scalability.

The Analytics Engineer will design data models, build pipelines, and ensure data quality to support AI evaluation and insights.

The AI-Native Data Engineer will build data pipelines, architect databases, design GCP infrastructure, and automate workflows for energy management using AI.

Develop and manage full stack big data applications, provide technical leadership, and collaborate with cross-functional teams to ensure integrated system processes.

Build scalable ML data pipelines for Waabi's autonomous driving platform. Design, optimize, and manage datasets and training processes while collaborating with scientists and engineers.

Design, build, and maintain scalable data platforms and pipelines using Azure Fabric, Databricks, and Snowflake. Optimize ETL/ELT workflows for reliability and performance, collaborate with analysts and scientists, ensure data security and compliance, and recommend improvements to data quality and analytics.

The Staff Data Engineer will design and build new data pipelines, improve data reliability, and collaborate with teams to deliver scalable solutions, while shaping the future of data engineering at CookUnity.

Responsible for bridging enterprise data with AI capabilities, translating business challenges into operational solutions, and driving complex sales deals by connecting technical solutions to business value.

The Senior Data Engineer will build and maintain the data platform, develop data pipelines, improve observability, and collaborate with teams in a cloud-based data environment.

The Senior Data Analytics Engineer designs and builds scalable data platforms, maintains ETL pipelines, optimizes SQL Server environments, and develops reporting dashboards to support data-driven decision-making.

As a Senior Software Engineer, you will develop and maintain software for healthcare applications, utilizing big data technologies and programming languages, ensuring high-quality code and system performance.

The Lead Data Engineer will architect and develop reporting solutions, integrate AI, analyze complex datasets, and mentor team members to enhance data-driven decision-making.

Designs and maintains scalable data pipelines and cloud data platforms, implements ETL/ELT and warehousing solutions, supports batch and streaming data, applies data governance and quality, integrates AI/GenAI capabilities, and collaborates with stakeholders to deliver analytics and data-driven insights.

As a Software Engineer in Data Infrastructure, you will build and maintain high-performance data storage systems for AI training, collaborate with experts, and optimize data processing.

The Senior Data Engineer designs, builds, and maintains data pipelines and ensures data quality controls while supporting data analytics and reporting needs.

Design, build, automate and maintain scalable ELT/ETL data pipelines and data architecture on cloud (AWS). Collaborate with analysts, data scientists and stakeholders to ensure data quality, governance, monitoring and performance. Apply ML-driven validation, anomaly detection, automated schema evolution and optimizations to support analytics and AI-native workloads.

Design, build, and maintain robust terabyte-scale data pipelines and stream-processing applications. Collaborate with product teams, participate in full SDLC, automate tests and deployments, monitor operations, and contribute to technical strategy and continuous improvement. Participate in on-call rotation.

Design, build, and operate large-scale real-time and batch data pipelines. Improve data quality, reliability, observability, and performance. Partner with product and analytics teams, lead architecture decisions, and support production incidents and optimization.

Design and deliver complex backend features for Informatica MDM within a microservices, cloud-native environment. Own end-to-end implementation, testing, architecture, reviews, and mentor junior engineers while collaborating with product and cross-functional teams.

The Senior Data Engineer II will design and operate data pipelines, manage data modeling, ensure data quality, and collaborate across teams for analytics and AI integration.