Top Data Analytics Jobs in Toronto

Design, develop, and maintain backend microservices for reporting, analytics, data export and data-driven features. Collaborate with product, data, and engineering teams, implement APIs for BI tools, ensure data quality/governance, participate in design reviews, mentor junior engineers, and support agile delivery.

Lead architecture and implementation of scalable analytics, reporting, and AI-driven data intelligence capabilities. Own end-to-end services, drive technical direction, mentor engineers, ensure operational excellence, and collaborate with product and design to deliver secure, high-performance, maintainable solutions using cloud-native and data-platform technologies.

Design, build, and maintain production data infrastructure and pipelines; automate workflows; enable cross-team data access; perform large-scale data wrangling, statistical analysis, and visualization to deliver business insights.

Provide legal leadership for Clarivate's corporate transactions including review and negotiation of deal documents, deal structuring, due diligence coordination, and general corporate projects. Support commercial agreement reviews when time permits, interact with senior executives, manage deal processes, and pursue ongoing professional development. Hybrid role with occasional travel.

Lead analysis of advisor, client, portfolio, sales, and operational data to produce actionable business intelligence. Build dashboards, scorecards, and executive reporting; conduct deep-dive analyses to identify trends, risks, and growth opportunities; partner with Sales, Operations, Technology, and leadership to translate requirements into scalable reporting and insights; support data governance and platform evolution to improve data quality and self-service BI adoption.

The Customer Success Manager will educate clients on creative strategy, build relationships, and help maximize their use of Motion's platform through engagement and tailored support.

Leads the enterprise workforce planning function, building forecasting, headcount, capacity, and scenario models. Partners with Finance, HR, Talent Acquisition, and business leaders on workforce costs, budgets, recruitment strategy, and planning governance. Owns workforce planning data infrastructure, pipelines, dashboards, and reporting, while redesigning manual processes into scalable systems. Influences senior stakeholders, delivers executive-ready analysis, and translates workforce data into strategic recommendations.

Design and build end-to-end data solutions and pipelines using modern cloud platforms; ingest, transform, and make data available for BI and downstream consumers. Partner with business stakeholders, implement CI/CD, testing, observability, and documentation, triage performance issues, and support delivery across client engagements.

The GTM Analytics Lead will drive data-driven decisions across marketing, sales, and finance, optimizing performance and ensuring sustainable revenue growth through analysis and real-time insights.

Lead end-to-end process mapping and analysis using BPMN and process/task-mining tools to identify inefficiencies, create As-Is/To-Be documentation, define BRDs, model future-state scenarios, and drive cross-functional implementation with executive reporting.

As a Senior Full Stack Software Engineer, you will own product features, design scalable systems, mentor teammates, and ensure coding excellence while collaborating with cross-functional teams.

Lead people-analytics strategy for Talent Acquisition and Talent Development. Drive end-to-end analysis of complex workforce problems, deliver evidence-based recommendations to senior leaders, ensure data governance and quality, coach junior analysts, build metrics frameworks, and conduct benchmarking and external research to inform workforce strategy.

Seeking an experienced Data Engineer to design and maintain data pipelines and infrastructure, collaborating with data scientists and stakeholders.

The Machine Learning Engineer will create scalable ML systems, build production data pipelines, and ensure robust deployment and monitoring of solutions.

Lead governance, maintenance, and enhancement of Anaplan and finance data processes. Ensure month/quarter close data integrity, support budgeting/forecast cycles, deliver reporting and ad hoc financial analysis, drive process improvement and automation, and manage a team of reporting/data resources while partnering across Finance, Technology, Data, and Risk stakeholders.

Lead growth analytics for wealth and insurance lines by turning client insights, market intelligence, and AI capabilities into strategies that drive acquisition, engagement, retention, and revenue. Partner with business, marketing, digital, technology, and operations to prioritize opportunities, develop business cases, measure performance, run experiments, and embed analytics into decision-making. Build and lead a high-performing analytics and growth team.

Analyze, extract, clean, and model large datasets from multiple systems; build data warehouses and predictive models; create financial analyses, dashboards, and client reporting; implement and monitor models with client teams; support client relationships and contribute to proposals and marketing as needed.

Perform end-to-end BI and data analytics work: extract and transform large datasets, build data warehouses and predictive models, create dashboards and reporting, manage client relationships, oversee analysts, and contribute to proposals and marketing as needed.

Build and maintain scalable analytics data models and transformation pipelines using dbt and data lakehouse technologies. Implement data quality, validation, and governance; optimize performance and cost; create documentation and tooling to enable self-serve analytics across product, ops, and AI teams. Mentor peers and collaborate with engineering and business stakeholders.

The Account Executive will develop and implement sales strategies, manage relationships with vendors, and drive growth through effective prospecting and client engagement.

As a Python and Kubernetes Software Engineer, you will develop data analytics solutions using open source tools, collaborating with a distributed team.

As an Engineering Manager, you'll lead a remote team, manage MLOps projects, ensure high performance, and mentor engineers while driving product strategies.

As Analytics Lead, you'll drive data-informed decision-making, lead measurement strategies, mentor teams, and oversee analytics infrastructure, impacting client strategies.

Lead marketing analytics as the architect of the data-driven growth engine: build BigQuery data schemas, predictive models (attribution, MMM, LTV), agentic AI monitoring, automated orchestration, executive BI, and target-setting frameworks to optimize demand generation and funnel quality across GTM.

You will manage a portfolio of accounts, working with marketing teams to optimize data usage, identify expansion opportunities, and facilitate onboarding and product fluency for eCommerce brands.