Top Data Analytics Jobs in Toronto

Own and build Motion’s outbound sales development function, including target lists, segmentation, messaging, channel strategy, pipeline generation, and SDR recruitment. Start hands-on by validating outbound playbooks, leveraging warm CRM data, AI-powered enrichment, signals, and automation, then scale the team. Coach SDRs on phone-based selling, establish predictable pipeline, and own sales development performance.

Architect and own marketing data infrastructure, including Databricks pipelines, Gold Layer tables, semantic models, and trusted analytics foundations. Lead cross-functional data initiatives, translate ambiguous business needs into scalable solutions, improve reliability and quality, and mentor engineers. Build and monitor production LLM and agent systems, automate workflows with AI, and deliver high-quality Python and SQL while validating AI-generated code. Partner with Marketing, Sales, BI, Data Science, and R&D teams.

Own marketing measurement workflows, including geo lift testing, custom analysis, reporting, attribution, and media mix modeling. Partner with media and client marketing teams to translate data into actionable business insights. Lead measurement consultations, influence marketing executives, educate nontechnical stakeholders, refine measurement playbooks, and contribute to service and product evolution.

Leads an eight-person analytics engineering team and sets strategy for trusted semantic models, governed data, enterprise BI, AI-powered data access, and production data applications. Oversees data modeling, evaluation datasets, telemetry, LLM routing, governance, security, and self-service capabilities. Partners cross-functionally to establish engineering standards, roadmaps, and measurable business impact while hiring, coaching, and developing team members.

Senior Analytics Engineer responsible for advanced data analysis, semantic layers, dimensional data models, dashboards, visualizations, and self-service reporting. The role partners with clients and cross-functional data teams to translate business needs into actionable insights, ensure data quality, and mentor junior analysts. Candidates need strong SQL, data modeling, ETL, database design, visualization, communication, and project management skills. Experience in consulting and healthcare, fintech, insurance, crypto, or retail is advantageous.

Own the end-to-end analytical function for a business unit such as growth, product, AI, or strategic partnerships. Define business problems, metrics, reports, analyses, and experiments; surface insights; and drive recommendations and decisions with cross-functional stakeholders. The role requires independent data work, strong SQL or Python skills, first-principles thinking, persuasive communication, and ownership of ambiguous problems through execution.

Own the analytical function for a core business area such as growth, product, AI and automation, or strategic partnerships. Define business problems, metrics, reports, analyses, and experiments; surface insights; make recommendations; and drive decisions and outcomes with cross-functional stakeholders. The role requires independent data work, strong problem solving, persuasive communication, and end-to-end ownership of ambiguous initiatives.

Own end-to-end business operations and analytics for a core business area such as growth, product, AI, automation, or strategic partnerships. Define business questions, establish metrics, build reports, conduct analyses and experiments, communicate insights, influence leadership decisions, and drive initiatives through execution. The role requires strong analytical thinking, independent data work, persuasive communication, and ownership of ambiguous problems.

Own the analytical function for a business unit such as growth, product, AI and automation, or strategic partnerships. Define business problems, metrics, reports, analyses, and experiments; communicate insights and recommendations; and drive decisions and outcomes with cross-functional stakeholders. The role requires independent data work, first-principles problem solving, persuasive communication, and ownership of ambiguous initiatives.

Develops business analytics, data science, dashboards, and AI-powered solutions for Corporate & Investment Banking. The role analyzes performance, cross-sell, client coverage, profitability, pipeline, and operating effectiveness using SQL, Python, Databricks, Power BI, and GenAI. Responsibilities include structuring ambiguous business problems, building scalable analytical assets, ensuring data governance, translating findings into executive recommendations, and partnering with senior stakeholders, Technology, Finance, Risk, and control teams.

Leads the architecture, development, and operation of scalable analytics, reporting, and AI-driven data intelligence services. The role drives technical direction, mentors engineers, owns complex initiatives end to end, and establishes engineering standards. Responsibilities include building distributed microservices, optimizing performance and reliability, implementing data quality and testing frameworks, collaborating cross-functionally, and using Python, Go, Kubernetes, GCP, and related technologies to support large-scale workloads.

Designs and delivers Master Data Management solutions for consulting clients. Defines solution architecture, data models, governance strategies, integrations, infrastructure, testing, and performance optimization. Advises business and technology teams, leads internal and partner resources, coordinates with project managers, conducts solution reviews and training, and supports implementation across multiple client engagements. Requires substantial MDM, Syndigo PIM, Java, database, consulting, project leadership, and business analysis experience.

Leads enterprise marketing measurement and analytics, including ROI, attribution, campaign measurement, reporting, and data foundations. Oversees Salesforce migration analytics requirements, data quality, KPI standardization, and scalable measurement solutions. Translates complex analysis into executive recommendations and manages a team of data scientists and analytics professionals while partnering across Marketing, Technology, data engineering, and business teams.

Conduct advanced analytics and statistical modeling for Retail Media Network campaigns, measuring attribution, ROAS, incrementality, and advertising effectiveness. Build predictive models, dashboards, reporting solutions, and automated analytical workflows using SQL, BigQuery, Python, Tableau, and Looker. Translate complex findings into actionable recommendations, manage analytical projects, document methodologies, collaborate with clients, and mentor junior analysts.

Develop and maintain Tableau and Looker dashboards, campaign performance reports, and automated reporting workflows. Analyze large datasets using BigQuery, SQL, Python, and statistical techniques to identify trends and actionable insights. Ensure data quality through profiling, cleansing, validation, and reconciliation. Collaborate with stakeholders to define KPIs, translate requirements into scalable analytical solutions, communicate findings, document workflows, and manage deliverables from development through deployment and maintenance.

Lead Strategyzer’s growth marketing engine across self-serve, team, and enterprise audiences. Set priorities, generate demand, improve website and customer journey conversion, manage lifecycle programs and experiments, and connect marketing activity to pipeline and revenue. The role requires hands-on HubSpot expertise, analytics, digital acquisition, AI and automation workflows, content judgment, and close collaboration with Product, Sales, the CEO, and subject-matter experts.

Leads procurement finance and analytics through cost modeling, market and award trend analysis, KPI reporting, budget reviews, scenario modeling, value engineering, and data/process improvement. Partners with Finance, Procurement, Operations, Estimating, and other teams to support sourcing and operational decisions. Manages cross-functional initiatives, ensures financial integrity and data governance, and presents cost insights, risks, forecasts, and recommendations to senior stakeholders.

Manages investment-related FP&A activities, including quarterly projections, peer benchmarking, cost allocation, operating plan analysis, and financial commentary. Serves as the FP&A subject-matter expert for Power BI, data modeling, analytics, automation, and scenario planning. Analyzes complex investment datasets, improves reporting and processes using AI and automation, establishes data quality controls, and collaborates with investment, finance, data, and technology teams.

Provides senior pre- and post-sales consulting for fraud, authentication, identity management, and AML/KYC solutions. Advises prospects and clients, develops solution proposals and demonstrations, supports implementation, analyzes models and performance, and delivers business insights. Acts as a subject-matter expert on fraud trends, industry requirements, data, and system interfaces. Coaches consulting and sales teams, contributes to product roadmaps, manages client relationships, and represents Equifax at conferences and marketing events.

Leads People Analytics, HR Technology, HR Systems, Master Data Management, and HR Service Delivery teams. Sets enterprise workforce intelligence strategy, establishes data governance and technology foundations, improves HR service delivery, and translates workforce insights into executive decisions. Requires senior HR leadership, multidisciplinary team management, HR technology and analytics expertise, operating model governance, Power BI knowledge, and enterprise platform experience such as Workday.

Build and maintain predictive models, including propensity-to-upgrade and engagement scoring, to drive AI product adoption and customer expansion. Develop features from product, behavioral, campaign, learning, and firmographic data. Partner with Marketing, Customer Success, Data Engineering, Product, and Commercial teams to operationalize models in Treasure Data and activation workflows. Monitor model performance, support experimentation, measure lift, document methodologies, and communicate insights to technical and nontechnical stakeholders.

Leads enterprise pricing and business analytics strategy, building pricing and financial models, predictive analytics, dashboards, data governance, and AWS-enabled data workflows. Translates complex data into executive recommendations that improve profitability and commercial performance. Oversees the analytics roadmap, partners cross-functionally with Operations, Sales, Marketing, and Finance, and hires and develops a high-performing analytics team.

Build and maintain PySpark and SQL data pipelines on Microsoft Fabric using medallion architecture. Develop automated reporting workflows, Power BI dashboards, DAX measures, and Power Query transformations for sales, churn, revenue, and commission analytics. Partner with stakeholders to deliver accurate data outputs, identify quality issues, eliminate manual processes, and implement AI-assisted automation. Document pipelines and data models to audit-grade standards while maintaining version-controlled artifacts.

Leads Faire’s Analytics Platform team, managing eight engineers and setting technical strategy for data warehousing, ETL/ELT pipelines, foundational datasets, BI tooling, governance, reliability, and cost efficiency. The role requires hands-on technical leadership, production issue management, AI-powered analytics tooling, cross-functional partnership, vendor management, and talent development. The manager will build scalable, trustworthy data systems used across engineering, data science, finance, product, and analytics.

Owns global marketing automation platforms, data architecture, audience segmentation, reporting, analytics, governance, and martech strategy for the Credit business. Designs automation programs, lead scoring, lifecycle frameworks, integrations, attribution models, KPIs, and executive dashboards. Analyzes campaign and funnel performance to deliver actionable insights and recommendations. Requires strong platform administration, marketing data management, visualization, project management, and stakeholder communication skills.