Top Data Analyst Jobs in Toronto

Lead and execute strategic data analyses for banking platforms, develop models and visualizations, drive analytics initiatives, consult with business clients, manage system changes from requirements to implementation, coach junior staff, and ensure data quality, risk compliance, and alignment between business and IT.

Senior Data Analyst partnering with Marketing to measure attribution, funnel performance, forecasting, and lifecycle metrics. Build analytical frameworks, scale AI-assisted analytics, work with cloud data stacks, BI tools, and martech to inform marketing decisions and improve data foundations.

Lead data governance for a major data platform project: define and enforce governance artifacts (access, metadata, quality, ownership), align SLAs and operational readiness, manage change and issues, enable stakeholders through training, and advise on report governance and compliance.

Design, deliver and maintain data and reporting solutions to support retail sales operations. Execute BAU tasks, document processes, test and reconcile metrics, respond to support requests, and gather stakeholder requirements to drive operational efficiency.

Support D2C and B2B growth by building automated dashboards, performing funnel and conversion analyses, tracking lifecycle marketing and ad performance, and partnering with cross-functional teams to scale growth initiatives. Learn from mentors and progress into owning growth and marketing analytics domains.

Lead analytics and operational insights for Customer Operations: define core metrics, build dashboards and forecasts, model churn/renewal risk, enable self-serve reporting, implement AI-enabled automation, and partner cross-functionally to drive retention, expansion, and support efficiency.

Support vehicle profitability analysis by developing automated COP/CMP-I models, dashboards, and forecasts using Power BI, Excel, and data techniques (regression, scenario modeling). Translate analytics into pricing and incentive insights, partner with IT to improve data quality, and drive process automation and forecasting for budgeting and strategic initiatives.

Lead design, development and delivery of data-driven regulatory reporting and BI solutions. Manage data quality and ETL processes, perform advanced analytics (statistical modeling, data mining, ML), produce reports/dashboards in PowerBI/Tableau, consult with stakeholders, and recommend data and reporting enhancements to support senior management decisions.

Gather, analyze, normalize, and validate disparate data files for upload into master data management systems. Support Purchasing, Sales, Sourcing, and Pricing with data guidance and analysis. Maintain product, vendor, customer, cost, and price files; identify automation opportunities; resolve data discrepancies and train or guide junior staff.

Ensure completeness, reliability, and controls of investment-related data and security master records. Maintain data quality, implement controls, resolve discrepancies with cross-functional teams, support reporting and audits, and contribute to data management initiatives (e.g., Aladdin MVP).

Lead enterprise data governance, policy, and resiliency programs. Define classification, retention, backup, immutability, and DR standards; translate policy into technical controls; design/operate backup and recovery across hybrid environments; lead DR exercises, testing, and audits; monitor compliance and drive continuous improvement; advise cross-functional stakeholders on data protection and resiliency strategies.

Perform product and player-behavior analysis for Marvel Strike Force using SQL/Python and reporting tools. Build recurring KPI reports, design/validate analytics tracking and experiments, partner with cross-functional teams, and use AI-enabled tools to accelerate workflows while ensuring data quality, privacy, and clear executive-ready insights.

The Senior Data Analyst leads analytical projects, collaborates with stakeholders, designs reporting solutions, and mentors junior analysts, focusing on data-informed strategies and decision-making.

The Product Analyst will oversee product analytics, collaborate with teams, define metrics, build dashboards, and improve data quality in a hybrid work environment.

As a Data Analyst at Stripe, you'll build data products, metrics, and dashboards, analyze large datasets, and communicate insights to drive business decisions.

Develop and run enterprise data governance: create and maintain policies, harmonize data, enforce standards, conduct audits, enable metadata/MDM/privacy practices, advise stakeholders, and align data strategy with business goals to ensure secure, accurate, and usable data.

The Forward-Deployed Data Analyst will engage with African Ministries of Health, build data management solutions, develop dashboards, and support public health decision-making.

Owner of end-to-end data analysis and delivery for product and client solutions. Design queries, datasets, reports and dashboards, protect recurring data deliverables, partner with Product/Sales/Technology, mentor junior analysts, and apply automation/AI to improve workflows and inform product strategy.

Lead data management and BI efforts for pension/member operations: design ETL and reconciliation processes, build dashboards and reports (Power BI/Tableau), resolve complex data integrity issues, support projects and UAT, train stakeholders, and drive remediation and audit activities to ensure accurate pension/member records.

Partner with Supply stakeholders to design and run analytical projects, build forecasts and statistical/ML models, run A/B tests, create dashboards and data products, automate manual processes, and deliver actionable insights to improve supply performance and operational efficiency.

Research, evaluate, and manage partnerships with data providers. Assess datasets for coverage and interoperability, support deal structuring, maintain partnership pipeline, and collaborate with product, engineering, and legal to integrate data into the platform.

Own end-to-end analysis of payments, chargebacks, and user lifecycle to identify drivers of net loss. Deep-dive into fraud cases, design and evaluate A/B experiments and risk-rule changes, build monitoring dashboards, partner with Risk, Payments, and Product to convert insights into mitigations, and run ad-hoc analyses of emerging loss trends.

Own enterprise data quality standards and monitoring across source systems, ETL pipelines, and cloud warehouses. Profile and validate data, perform root-cause analysis, design ETL test strategies, and prevent bad data from reaching models and dashboards. Partner with Data Engineering, Data Science, and Governance to define validation criteria, report KPIs, and mentor junior analysts.

Support daily market reference data operations for investment systems: investigate and resolve data exceptions, validate pricing and valuations, document procedures, support change initiatives and testing, and collaborate with stakeholders to improve data quality and controls.

Lead product-focused analytics for seller and listing performance: define KPIs, build/maintain data models and ELT pipelines, run experiments and impact measurement, deliver dashboards and automated reporting, use AI-assisted tools and analytics agents, and mentor junior analysts to drive business outcomes.