Top Data Analyst Jobs in Toronto

Serve as the functional expert for SAP financial data, ensuring data integrity and alignment with P&L/Balance Sheet. Support SAP BW-IP planning, Power BI and BW reporting, troubleshoot complex issues, optimize BW data models, and enable integrations with modern data platforms like Databricks and OneStream.

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 Staff Data Analyst will lead data strategy for Compliance, analyzing regulatory engagements, and driving effectiveness through actionable insights and collaboration across various teams.

Lead marketing analytics and data strategy for B2B SaaS Marketing. Design measurement frameworks, own attribution, funnel and lifecycle analysis, forecasting, and marketing investment recommendations. Partner with senior marketing leaders and cross-functional teams to build data foundations, enable AI-assisted analytics, and mentor analysts to raise analytical standards.

Deliver accurate, timely workforce reporting and insights for HR and business partners. Maintain data quality, enforce reporting governance, automate recurring reports using Excel/Power Query, support HR systems (Dayforce/Workday/etc.), validate data, and partner with stakeholders to improve reporting processes and data literacy.

Build and optimize enterprise ETL/ELT pipelines, data platforms, warehouses, models, and integration processes. Ensure data quality, governance, lineage, security, and performance across systems. Develop AWS-based data solutions and support automation, CI/CD, infrastructure as code, and monitoring. Partner with business and technical stakeholders to translate requirements into scalable solutions and deliver reliable analytics and reporting. Financial services knowledge and occasional travel may be required.

As a Data Analyst, you will analyze user behavior and product performance, creating reports and dashboards to aid decision-making and optimize user experience.

Partner with the Self-Serve product team to measure and optimize the acquisition-to-engagement funnel. Build reusable datasets and dashboards, validate instrumentation, run deep-dive analyses and experiments, and translate insights into narratives for technical and non-technical stakeholders to inform product and go-to-market strategy.

Design, build, and govern Float's dashboards, metrics, and self-serve BI. Translate business questions into durable data products, validate dbt models, reduce ad-hoc requests, and use AI to scale analysis and accessibility for Finance, RevOps, GTM, and leadership.

Lead analytics for Zynga Poker by running A/B tests, building ETL pipelines and dashboards, analyzing player behavior, tuning game economy, and improving fraud/bad-actor models. Collaborate with product, design, and data science teams, contribute to AI/LLM initiatives, and maintain telemetry and BI tools to inform strategic decisions that impact millions of players.

Analyze sales, pricing, margin, customer, and operational data to produce actionable commercial insights. Build and maintain Power BI, Tableau, and Excel dashboards, automate reporting, track KPIs, support forecasting and demand planning, and identify trends and profitability opportunities. Partner with Sales, Marketing, Finance, Operations, and IT to improve data quality, CRM and ERP integrity, governance, and reporting processes while communicating findings to nontechnical stakeholders.

Support client analytics initiatives through exploratory analysis, dashboarding, KPI tracking, recurring reporting, data quality validation, and insight communication. Translate business questions into analytical requirements, document metrics and processes, collaborate on data modeling and reporting layers, and identify workflow improvements. The role also provides exposure to digital consulting, product development, user experience, and data governance.

Analyzes operational data to identify trends, risks, bottlenecks, and improvement opportunities. Builds and maintains Power BI dashboards, scorecards, and scalable reporting solutions covering performance, efficiency, quality, service levels, and capacity. Partners with Operations, Process Improvement, and Technology teams to improve data quality and usability, establish reporting governance, and provide executive-ready insights and recommendations that support operational decision-making.

Analyzes business needs and translates them into system, data, reporting, and process solutions. Responsibilities include requirements gathering, process mapping, ERP support, application configuration and testing, vendor coordination, UAT, dashboards, operational reporting, KPI development, IT support, cybersecurity assistance, and staff training. The role requires collaboration across business and technical teams in a regulated environment and is a 12–18 month, five-days-per-week on-site maternity leave coverage position.

Perform product-focused analyses and A/B tests to generate actionable insights; build dashboards and KPIs; ensure data quality; synthesize diverse data sources; present findings to stakeholders and senior leadership to guide product and business decisions.

Analyze large datasets to produce dashboards, metrics, and insights supporting product, care, and business decisions. Build BI infrastructure, run A/B and multivariate tests, perform ad-hoc analyses and visualizations, and collaborate with stakeholders and data scientists to inform strategy and operations.

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

Analyzes pipeline, funnel conversion, campaign performance, retention, and revenue drivers across Sales, Marketing, and Client Success. Builds and maintains dbt models, data marts, quality controls, documentation, and BI-as-code assets using Salesforce and modern data-stack technologies. Partners with stakeholders to turn ambiguous questions into decisions and advances AI-agent workflows for faster analytics and reporting.

Lead the RTB reporting sub-team to ensure accurate, reliable finance and compliance reports. Build repeatable processes, documentation, and automation; own stakeholder relationships; mentor juniors; and drive cross-functional reporting initiatives from definition through execution.

Support driver earnings and marketplace teams with SQL-driven analysis, reporting, and financial reconciliation. Provide insights, track product performance, support experiments, prepare leadership business reviews, and develop processes and playbooks to improve earnings products and reduce errors.

Lead investment data governance by designing and operating data quality controls, reconciling and troubleshooting investment system data, administering reference/security master and pricing data, managing vendors, supporting front-office/trading applications, and participating in system releases and MDM activities to ensure accurate, timely data for investment decision-making.

Design, prototype, and deploy advanced visualizations and machine learning models for segmentation, personalization, churn prediction, LTV forecasting, and marketing optimization. Partner with stakeholders to define problems, lead end-to-end data science projects, adopt emerging tools, improve analytics workflows, communicate insights to varied audiences, and mentor peers to set technical standards.

Lead analytics for Internal Audit Claims: extract, transform, reconcile, and validate large claims datasets; build and maintain Power BI reports/dashboards; perform QA and tie-outs; support automation, bots/AI enablement, and executive reporting; mentor other analysts and partner with audit, IT, and business stakeholders to deliver repeatable, validated analytics.

Analyze player behavior, game health, engagement, retention, monetization, and live-service performance for Marvel Strike Force. Own KPI reporting, explain trends and variances, evaluate experiments, validate analytics tracking, and deliver actionable insights to product, design, marketing, live operations, and leadership teams. Use SQL, Python, reporting tools, and AI-enabled workflows while maintaining data quality, privacy, and analytical rigor.

Drive data analytics for a warehouse design platform: clean and analyze large, messy supply chain datasets, identify repeatable patterns, build prototypes and visualizations, and translate insights into product features to automate manual spreadsheet work.