Top Data Jobs in Toronto

Design, build, and manage Northland's Azure-based enterprise data platform. Lead data architecture, develop scalable ETL/ELT pipelines, model enterprise data, ensure data quality and governance, deliver self-service data marts and Power BI datasets, and provide technical leadership to support analytics and AI initiatives.

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

Use real-time and historical healthcare data to prepare, analyze, visualize, and report on metrics and trends. Build and update Tableau dashboards, write complex SQL queries, extract and clean data, provide insights and recommendations, respond to ad hoc requests, and collaborate with internal and external stakeholders.

Design, develop, test and support finance data solutions using Azure, Databricks, Python and Spark. Lead technical design, implement metadata-driven data pipelines and Bronze/Silver/Gold data lake patterns, support CI/CD DevOps processes, coordinate with finance stakeholders and vendors throughout implementation and delivery.

Contributors record authentic first-person video of household tasks, hands-on work, and everyday activities using a phone mounted to a headstrap. They choose their own schedule, preferably recording at least 10 hours weekly, then upload footage through Perle’s app for review and payment. Contributors must be at least 18, reside in the United States, Canada, or Latin America, have a supported smartphone, and be comfortable wearing a headstrap.

Analyze microbiome and longitudinal clinical datasets, develop microbiome metrics and biomarkers using statistics and machine learning, create visualizations and reports, draft clinical research documents, support product and study development, and contribute to scientific publications and proposals.

The role involves designing and building data pipelines for analyzing user feedback on AI models, ensuring data quality and infrastructure scalability.

As a Data Engineer, you will develop and manage data pipelines, ensuring reliable data ingestion and delivery while optimizing for simplicity and performance.

Design and maintain data warehouse systems, develop ETL pipelines, manage datasets for analytics, and implement real-time data solutions.

The Data Scientist will design algorithms for insights, structure data, collaborate with machine learning engineers, and analyze datasets to improve workflow automation and product value.

The role involves programming and data review for real-world data analysis, supporting epidemiologists, and managing complex data sets using statistical programming languages and tools.

The Data Analyst will build key data models and metrics for decision-making, partner with stakeholders for analytical insights, create datasets for self-service reporting, and ensure data reliability through quality checks.

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

Lead a team in developing scalable data solutions, mentor engineers, manage expectations, and contribute to code. Focus on high-quality software practices.

Design and run evaluation frameworks to assess third-party vendor data for fraud detection. Build lift analyses, backtests, and champion/challenger tests; profile vendor datasets for quality and coverage; collaborate with fraud, product, and data engineering to define ingestion and testing requirements; translate findings into actionable recommendations and maintain an internal knowledge base; support ad hoc analyses on fraud trends and model performance.

Lead enterprise Data & AI transformation initiatives, managing the delivery of cloud-based analytics platforms while aligning business and technology objectives. Responsibilities include program governance, stakeholder management, and overseeing implementations of Microsoft Fabric.

Design, build, and optimize cloud-based data platform components: ingest and transform varied datasets, create metadata-driven pipelines and data APIs, support AI/ML infrastructure, implement monitoring and metrics, and improve data processes to enable analytics and operational systems.

The Senior Data Scientist will build frameworks for data-driven decision making, develop predictive models, ensure data quality, and enhance customer experiences through analytics and operational insights.

The Director of Data Strategy will develop and execute a data strategy, ensuring data quality and governance across the organization, fostering collaboration among various departments for improved analytics and business outcomes.

Perform clinical data management for Phase I-IV studies: design and test eCRFs/EDC, develop edit checks and DMPs, manage queries, reconcile external data and SAEs, support database lock, and collaborate with cross-functional teams and vendors.

The Strategic Customer Representative drives growth within data centre construction sectors, manages client relationships, and coordinates projects with multiple stakeholders.

Build and maintain scalable, reliable data systems and pipelines, uphold SLOs, partner with Product/Sales/Finance, enable self-service analytics, contribute to data platform strategy, and improve engineering practices for testing, reliability, and documentation.

The Senior Data Platform Engineer will design and operate a unified data platform, ensuring reliable data flows and collaborating across teams to shape data strategy and architecture.

Perform data extraction, transformation, cleansing and imports (CSV/SQL) into Clio, support customer onboarding, troubleshoot escalated migrations, manage multiple client cases, create knowledge articles, partner with enablement and product teams to improve and automate migration processes, and deliver exceptional customer service throughout the migration lifecycle.

Embed with a business unit to define analytic problems, build metrics/reports, run analyses and experiments, surface insights, and drive data-informed decisions end-to-end using SQL/Python.