Top Data Jobs in Toronto

Wayvia is building a talent pipeline for engineering roles focusing on backend systems, data pipelines, and product engineering. They seek curious and collaborative engineers to connect with and solve future challenges.

Design and build scalable data systems and pipelines, migrate legacy systems, ensure data governance, and collaborate with cross-functional teams to enhance data accessibility and reliability.

The Senior Software Engineer will manage data systems, develop scalable pipelines, ensure data security, and build self-service applications for users at Coinbase.

The Product Manager will lead the identity platform, focusing on improving data quality, performance, and business outcomes through cross-functional collaboration and effective communication.

As a Senior Associate, Data Analyst at Capital One, you will analyze datasets to support business strategies, communicate insights, and enhance decision-making through data visualization and stakeholder collaboration.

The Product Manager for Data Products at Capital One will drive the design and operationalization of data products, prioritizing long-term roadmaps, defining metrics-driven strategies, and collaborating across teams to enhance customer experiences.

The Enterprise Architect leads the development of AI and Data architecture, aligning technology with business needs while ensuring adherence to governance standards. They provide strategic guidance, collaborate with stakeholders, and utilize advanced technologies to enhance solutions and processes.

The Container Optimization Marketing Manager will strategize and execute marketing initiatives to drive growth and pipeline for DoiT's Kubernetes solutions, ensuring competitive market positioning and measurable revenue impact.

The Senior Staff Software Engineer will architect Affirm's lakehouse analytics platform, implement data governance, mentor engineers, and collaborate cross-functionally to optimize data infrastructure and solutions.

CommBank is seeking Indigenous job seekers for various roles across its sectors, offering traineeships, internships, and direct employment opportunities with support from an Indigenous Careers team.

Design, build, and operate production ML signal systems—ranking, retrieval, recommendations, propensity, and next-best-action—covering feature/candidate generation, serving, experimentation, monitoring, and feedback. Define signal contracts (freshness, provenance, confidence), evaluate long-term impact (trust, fairness, compliance), and partner across product, data, and risk teams to deliver reusable customer-intelligence capabilities.

Own strategy and roadmap for Spotify's data catalogue, metadata, and lineage. Prioritize user needs, deliver solutions (build/buy/integrate), define KPIs, collaborate with engineering, design, and data teams, and influence stakeholders to improve data discoverability, governance, trust, and AI-driven workflows.

The Lead Data AI Architect leads the design and implementation of secure data and AI architectures, guiding teams on best practices and managing compliance with business strategies and technical standards.

The Data Operations Manager will oversee the HCP Access data product lifecycle, ensuring data quality and customer deliverables through monitoring, validation, and process optimization in collaboration with technical teams.

As a Senior Data Engineer at Nimble, you will manage the end-to-end data platform, build pipelines, enhance data modeling, collaborate with teams, ensure data security, and mentor others.

This role involves designing and developing scalable data solutions, automating tasks, and collaborating with teams to deliver business value. Responsibilities include strong database development using SQL and Python, as well as leading innovative projects and ensuring compliance.

As a Senior Software Engineer, you will drive high-impact initiatives in data engineering, mentor junior team members, and build scalable, customer-facing applications. You will collaborate with cross-functional teams to enhance product features and contribute to the team's vision.

Design and deliver analytical measurement frameworks, causal inference and experimental designs, and predictive/statistical models for retail, loyalty, and marketing analytics. Build and validate tests, analyze large datasets, collaborate cross-functionally, and communicate insights to improve customer engagement and program performance.

Lead workforce, capacity, and budget analysis to deliver reporting, variance insights, and actionable recommendations. Build forecasts, promote self-serve reporting, document data and workflows, and implement automation using Power Platform, Power BI, and Azure Databricks to improve staffing, cost efficiency, and operational decision-making.

Maintain and create product master data across PIM/ERP/Oracle systems; collaborate with cross-functional teams and suppliers; manage pricing/promotions, data quality, incident management, process documentation, and produce product/inventory/sales reports to support supply chain and merchandising.

Lead and build a hands-on data science and analytics function for a live-service gaming company. Own analysis (SQL, Python/R), dashboards, KPIs, experimentation, data quality, pipelines, and executive reporting. Partner across product, ops, marketing, finance and engineering. Implement AI-driven analytics, automation, and copilots, then hire and scale a high-performing team while establishing governance and responsible AI practices.

Lead a team to align and maintain client data across Capital Markets applications, overseeing sales coverage, client hierarchies, corporate actions and ongoing data maintenance. Drive data governance, quality, controls and operational efficiencies by partnering with Front Office, Operations, Technology, Legal and Compliance to ensure accurate, complete data for lifecycle management and regulatory reporting.

Design and deliver data analytics and AI solutions for Capital Markets. Apply statistical and machine learning models, build AI agents and dashboards, produce insights for senior management, and collaborate with data engineers and business teams to ensure governance and integration.

The Data Analyst will analyze large datasets, collaborate with stakeholders, develop data processes, and support data-driven decision-making to improve business efficiency.

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