Top Data Analyst Jobs in Toronto

Lead measurement, monitoring, and diagnostic reporting for AI-powered personalization models. Build scalable data pipelines in GCP and BigQuery, develop automated alerts, support A/B testing, and create Tableau visualizations. Evaluate recommender systems and propensity models using statistical and predictive analytics, integrate insights into AI products, and communicate findings to technical and non-technical stakeholders while mentoring junior team members.

Maintains vendor master data across ERP systems, supporting supplier onboarding, data creation, maintenance, deactivation, issue resolution, synchronization, audits, and compliance. Produces KPI reports, dashboards, and analyses; identifies root causes and process improvements; maintains governance standards and documentation; supports data-loading tools; facilitates meetings; delivers training; and collaborates with suppliers, hospitals, and internal teams.

Produce quarterly Viva Engage and Microsoft 365 analytics reports, validate and package data in Excel and PowerPoint, respond to ad hoc requests, support communications stakeholders, and improve reporting methodologies. The role serves as a secondary analytics subject matter expert, researches measurement best practices, and helps reduce routine reporting demands on senior analytics staff.

Manages and validates pension member data received from employers, including interface processing, reconciliation, correction, investigation, and database support. Performs user acceptance testing, maintains spreadsheets and project files, supports pension-related special projects, and improves data control procedures. Communicates with employers and internal teams about data requirements and system issues while identifying trends, resolving problems, and recommending process improvements.

Designs and maintains data controls, quality rules, ETL processes, governance, and source-to-target mappings for financial crime and risk systems. Leads complex data initiatives, troubleshoots database and pipeline issues, performs profiling and root-cause analysis, automates processing, and develops data quality metrics. Collaborates globally with business, technology, development, and testing teams. Requires extensive PL/SQL, data management, AML transaction monitoring, cloud data lake, Python, distributed query, database, payments, and financial systems experience.

Leads business intelligence and data analysis initiatives by examining scientific and operational datasets, developing KPI insights, mapping business and data processes, and conducting deep-dive analyses. Engages stakeholders, translates requirements into user stories, leads requirements workshops and UAT, validates data, creates process and data-flow diagrams, and collaborates with engineering, product, and business teams to deliver analytics solutions.

Develop and maintain ETL/ELT data pipelines and data infrastructure within a cloud-centric data lakehouse environment. Responsibilities include pipeline design, development, testing, documentation, operational support, business requirements analysis, proof-of-concept implementation, reporting, and BI semantic-layer support. The role requires advanced SQL and Python/PySpark expertise, cloud and database experience, knowledge of Delta Lake, Spark, Parquet, data architectures, and privacy and security compliance.

Manages reinsurance data quality, administration, reporting, and operational systems support. Analyzes complex data, investigates issues, develops controls, supports system configuration and testing, and improves processes. Serves as the Canadian Omega subject matter expert, partners with cross-functional stakeholders, supports audits and implementations, and translates business requirements into operational and technical solutions. Provides guidance, documentation, training, and mentorship while supporting reinsurance billing, claims processing, integrations, and reporting enhancements.

Support client analytics initiatives by translating business questions into analytical requirements, analyzing data, building dashboards and recurring reports, tracking KPIs, validating data quality, and communicating insights through visualizations and presentations. Collaborate with engineers, analysts, and stakeholders on data modeling, reporting layers, analytics processes, and workflow improvements while developing broader consulting and digital product skills.

Analyze identity, access governance, and authentication data to identify trends, anomalies, control gaps, and reporting issues. Build dashboards, reconcile data from IAM platforms, support IAM operations, and provide recommendations that strengthen access governance, audit readiness, and reporting accuracy. Collaborate with Identity Management, Cybersecurity, Technology, Risk, Internal Audit, and business stakeholders.

Analyzes complex datasets using advanced statistical methods, experiments, predictive models, forecasting, segmentation, and regression. Develops measurement frameworks, KPIs, and reproducible workflows; integrates and validates large datasets; and translates findings into actionable recommendations for clients and internal teams. The role partners on optimization and go-to-market strategies, communicates insights to technical and non-technical audiences, and supports client meetings and occasional field ride-alongs.

Analyzes complex datasets and applies advanced statistical methods to evaluate marketing programs, customer behavior, sales performance, and promotional effectiveness. Develops KPIs, measurement frameworks, experiments, predictive models, and reproducible workflows. Translates findings into actionable recommendations for clients and internal stakeholders, supports data-driven go-to-market strategies, and communicates insights to technical and non-technical audiences using Python, R, SQL, and visualization tools.

Maintains and validates inventory master data across regions and systems, ensuring accuracy, completeness, standards compliance, and duplicate prevention. Loads and configures inventory items in Oracle Fusion and JD Edwards, assigns organizations, pricing groups, and cycle counts, and aligns item numbers across systems. Supports supply chain solution implementations, upgrades, rollouts, troubleshooting, and end-user testing while collaborating with regional and cross-functional teams. Requires three or more years of relevant experience, strong analytical and administrative skills, and willingness to travel globally as needed.

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.

Own marketing analytics, funnel reporting, dashboards, attribution, cohort analysis, and conversion rate optimization. Analyze customer journeys from acquisition through retention, identify funnel losses, and design and evaluate A/B and multivariate experiments across landing pages, signup, onboarding, and email. Partner with marketing, product, engineering, RevOps, sales, and leadership to improve measurement, define trusted metrics, and translate findings into prioritized growth recommendations.

Supports client analytics engagements through dataset analysis, dashboard and report development, KPI tracking, data validation, documentation, visualization, and communicating insights. Collaborates with senior analysts and data engineers while developing consulting, data modeling, reporting, and analytical workflow skills.

Analyze complex enterprise data and translate business needs into scalable reporting, dashboards, and business intelligence solutions. Lead discovery sessions, define analytical requirements and success metrics, write advanced SQL, develop self-service analytics using BI platforms, and communicate actionable insights to stakeholders. The role also applies data storytelling, process optimization, AI-enabled analytics, and emerging technologies to improve decision-making and operational performance.

The Data Analyst will translate business needs into scalable analytics solutions, develop dashboards and business intelligence using tools such as Looker or Tableau, write advanced SQL, analyze enterprise data, and communicate actionable insights. Responsibilities include leading discovery workshops, defining metrics, improving business performance through trend and root-cause analysis, supporting self-service analytics, using AI-enabled tools, and identifying opportunities for process and analytics innovation.

Develop Tableau dashboards, perform advanced data analysis, and present actionable insights to Capital Markets stakeholders. Partner with senior leaders to identify revenue and cost-saving opportunities, optimize processes, support analytics roadmaps, and prioritize projects. Use SQL and large-scale databases, explore data visualization and mining tools, and collaborate with data science and marketing analytics teams to deliver business value.

Develop and maintain data governance workflows, compliance processes, and model lifecycle practices for RESL. Analyze structured and unstructured data, apply feature engineering and model interpretability techniques, write maintainable Python code, and collaborate with cross-functional teams to align governance requirements. The role also supports process improvement, standardized workflows, analytical problem-solving, and implementation of data and model management best practices.

Senior Business Analyst responsible for gathering and analyzing business requirements, evaluating data and processes, supporting technology and project teams, developing project documentation, designing functional solutions, and validating requirements through test cases and end-user testing. The role provides analytical and technical consulting, identifies process and system improvements, delivers insights and recommendations, and supports commercial risk decisions within BMO’s risk management framework.

Partners with operational teams to identify process improvement, automation, and AI opportunities. Leads discovery, requirements gathering, solution design, and deployment using Microsoft Copilot, Power Platform, SharePoint, and related tools. Develops reporting, AI agents, and automation solutions while ensuring security, privacy, and governance. Supports adoption through training and change management, and measures outcomes including efficiency, cost savings, capacity creation, and user adoption.

Supports daily investment data operations across market reference data, pricing, benchmarks, security master, and related domains. Validates data quality, monitors exceptions and reconciliations, investigates issues, maintains records, and coordinates with investment, technology, risk, finance, governance, and vendor partners. The role also supports testing, system upgrades, documentation, controls, and process improvements while ensuring accurate and timely operational data.

Leads analytics support for international sports fan growth and engagement. Partners with marketing, club, league, and regional stakeholders to define analytics opportunities, perform SQL and Python analysis, develop segmentation, propensity, churn, forecasting, and customer lifetime value models, and translate findings into business recommendations. Owns reporting and data quality, presents to senior audiences, mentors analysts, coordinates team priorities, and collaborates with data engineering and external partners.

The Senior Data Analyst develops business intelligence reporting, dashboards, visualizations, data models, and analytical data assets using Power BI, SQL, and Python. The role monitors portfolio performance, reconciles data, identifies trends, creates executive-level insights, and supports strategic initiatives. Responsibilities include stakeholder consultation, requirements gathering, data storytelling, governance-compliant reporting, documentation, and technical ownership of analytics projects.