Top Data Jobs in Toronto

The AVP, Cyber & Data Risk at Aviva Canada will lead oversight of data privacy, governance, and cybersecurity, driving effective risk management and compliance initiatives across the organization.

Lead the strategy and execution of Beacon's data platform, integrating technology stacks and developing AI-powered workflows to support BD and M&A functions.

As a Data Engineer, you'll develop and manage data ingestion pipelines, model data for analytics, and ensure data quality across advertising platforms.

Support the development and enforcement of data governance policies and standards. Collaborate with stakeholders to enhance data quality and compliance while managing data governance projects.

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

Lead end-to-end data migration testing for a large financial-services transformation. Own test strategy, define scope and entry/exit criteria, validate mappings and ETL, manage reconciliation/validation, oversee defect management, ensure auditability for regulators, and report status, risks, and metrics to stakeholders.

The Account Executive at CoStar is responsible for selling new business, managing client portfolios, and driving growth through the entire sales process in the commercial real estate sector.

As a Senior Data Scientist, you will design AI solutions, lead NLP implementation, and mentor junior staff while transforming data into actionable insights.

Analyze complex datasets, build interactive dashboards, run predictive and statistical analyses, enforce data governance, automate reporting, and partner cross-functionally to deliver actionable insights.

Use advanced analytics, statistical testing, and machine learning to optimize onboarding, activation, and Next Best Action strategies. Build dashboards and automated reports, analyze campaigns and customer journeys, collaborate with cross-functional teams, and translate insights into actionable recommendations to improve engagement, profitability, and risk outcomes.

Execute and document complex testing, monitoring and operational activities for credit/data controls. Analyze data to provide insights and recommendations, identify root causes, support change management and continuous improvement, and maintain stakeholder relationships to ensure timely, compliant service delivery.

Lead front-end analysis for data and analytics initiatives: define solution intent, assess feasibility and data quality, perform SQL profiling and source-to-target mapping, document data definitions and business rules, identify risks, and support delivery, adoption, and reporting across business and technical stakeholders.

Lead enterprise data, analytics, AI, automation, and information governance. Define strategy and roadmap, modernize data platforms (lakehouse/Azure Databricks), establish AI and automation capabilities, enforce governance/MDM (Semarchy), deliver BI/Power BI and predictive solutions, run Automation CoE, drive data literacy, and build a high-performing cross-functional team.

Design and implement scalable data ingestion and onboarding pipelines, build automation and Claude-powered tooling to reduce production MTTR, integrate third‑party sources (Veeva/Salesforce), design APIs and warehouse schemas, and collaborate cross-functionally to deliver production-grade data solutions on AWS and Snowflake.

Build and maintain real-time and batch data ingestion and transformation pipelines using AWS and modern data tools. Design data models, consolidate sources into data lakes/warehouses, collaborate with engineers on data integrity, produce prototypes for unknown solutions, and support deployment of data models and dashboards for analytics and visualization.

Lead design and administration of enterprise backup, recovery, and cyber-resiliency using Veeam, Commvault, and AvePoint. Drive data governance, classification, retention, and Microsoft Purview initiatives. Support DR/BCP planning, recovery testing, cloud and on-prem platforms, and mentor junior staff while ensuring compliance and audit readiness.

Design and implement data warehousing solutions on Microsoft Azure. Build ETL pipelines, develop data models and advanced SQL queries, gather and document business requirements, maintain data documentation, and collaborate with Agile teams and stakeholders to ensure data quality and drive data-driven decisions.

Design and build ML and deep learning models, perform large-scale data analysis and EDA, collaborate with engineers and product teams on ETL and data solutions, provide data-driven recommendations to business stakeholders, and scale analytics into production-ready solutions.

Design and build predictive models and machine learning solutions using big-data technologies. Mine structured and unstructured data, develop end-to-end scoring pipelines, collaborate with product teams and stakeholders, and provide data-driven recommendations to senior leaders to improve customer experience and business outcomes.

Design, build, and maintain scalable data pipelines and infrastructure using Spark, Kafka, cloud platforms and containerization. Ensure data integrity, ETL, high availability, performance tuning, observability, and collaborate with AI/data science teams to enable analytics and ML solutions.

Lead finance-focused data standards, controls, and Chart of Accounts optimization. Gather requirements, translate needs into functional specifications, coordinate cross-functional projects, support QA/testing, assess impacts, and drive process improvements and change management with finance and IT stakeholders.

Design and optimize scalable ETL pipelines and enterprise data warehouse solutions to support omnichannel analytics and AI products. Collaborate with analysts, engineers, project managers, and clients to gather requirements, deliver BI dashboards and integrations (Power BI, Fabric, Tableau), ensure data quality, and standardize engineering practices including Git, documentation, and reusable code.

Design, develop, and maintain scalable Databricks-based ETL/ELT data pipelines and transformations. Support migration from HANA to a modern lakehouse, ensure data quality and performance, troubleshoot issues, participate in code reviews, and collaborate with architects, analysts, and stakeholders to deliver enterprise reporting, analytics, and AI-ready data solutions.

Work with product, engineering, and analytics to detect fraud and improve payments by designing and analyzing experiments, building ML models and data pipelines, monitoring product health, and translating insights into action to protect riders and drivers.

Lead and evolve spatial data standards, governance, and processes; translate spatial and occupancy data into business value; partner with technology teams for implementations; modernize methods and playbooks; advise clients and support practice growth across regions.