Top Data Jobs in Toronto

Design, build, and maintain scalable data systems and pipelines; ensure SLOs and reliability; partner with Product, Sales Ops, and Finance to deliver analytics; support self-service tooling; contribute to data architecture, testing, and documentation.

The Director, Data Analytics & Insights leads data analytics strategies and teams, ensuring data-driven decision-making while collaborating with stakeholders across the organization.

The Senior Data Analyst will manage client-facing reports, ensuring data quality and building reliable analytics products while collaborating with various teams.

The Principal DataOps Engineer will optimize cloud-based platforms through CI/CD automation, lead a small team, and drive data-driven decision-making across the organization.

The Senior Data Analyst will enable strategic decision-making through data analysis, reporting, and collaboration with stakeholders to ensure high-quality data integrity.

The Data & Deployment Engineer coordinates EMS software and data pipeline deployment, manages CI/CD processes, and supports integration between data and hardware teams, ensuring project success.

As a Data Engineer, you will design and build data infrastructure, ensuring data continuity, modernizing data systems, and collaborating with teams to optimize data workflows.

The Compliance Analyst will support compliance projects, ensure regulatory adherence, analyze financial data, and collaborate with various teams to maintain compliance standards.

The Director of Product for Data Flywheel will lead the roadmap for data initiatives, ensuring quality and compliance across various engineering teams and initiatives. Responsibilities include managing data metrics, supporting data pipelines, and collaborating across teams to enhance infrastructure.

Design, build, and maintain scalable data pipelines and models on Databricks/Spark; create dashboards; enable AI-powered features; troubleshoot data quality and performance; drive automation and end-to-end project ownership.

Design and build modern data solutions, collaborating with clients and teams, while focusing on effective data architecture, engineering, and ETL development.

Build and scale batch and real-time data pipelines, automate cloud infrastructure and CI/CD, develop ETL and analytics, create reports and dashboards, and partner with stakeholders to deliver data-driven insights.

The Data Engineer I will design and implement data solutions on Azure, developing ETL processes, managing data pipelines, and ensuring data quality and security, while collaborating with various teams.

The Analyst, Data Management ensures data reliability and completeness for investment-related records, coordinating with teams on data quality and compliance.

As a Data Scientist on the Mapping team, you'll enhance route recommendations and travel time estimations by analyzing spatial data and building robust models to improve mapping products.

Design and manage distributed data systems for processing and transforming datasets for AI model training, ensuring data quality and scalability.

The Senior Geo Data Scientist will develop advanced machine learning models for geospatial data, build scalable data pipelines, and enhance model performance for mineral exploration.

The Senior Data Engineer will scale the data ecosystem, construct data models, build systems for KPI tracking, and ensure data safety.

The Data Analytics Manager will lead a team in analyzing ad inventory and performance metrics, developing insights to inform strategy, and enhancing data infrastructure.

Responsible for managing a data engineering team, overseeing data pipelines and platforms, and ensuring the efficient processing of high-volume data. Focus on mentoring, project management, and optimizing system performance.

The Senior Data Scientist will analyze complex datasets to provide insights into medical information, support product development, and mentor analysts, fostering data-driven decision-making across the organization.

As a Data Engineer, you'll design and maintain ETL pipelines, develop Airflow DAGs, and collaborate with analysts to ensure data quality and delivery.

The Data Governance Lead will oversee data governance frameworks, manage metadata, ensure data quality, and collaborate with stakeholders on data policies.

The Data Engineer will design, develop, and maintain data pipelines in the banking domain, ensuring data quality and compliance while collaborating with stakeholders.

The Data Engineer will design and maintain data models and ETL pipelines, support data strategy initiatives, and ensure data quality within an Azure environment.