Top Data Jobs in Toronto

Design, build, optimize, and monitor scalable data products, pipelines, APIs and analytics solutions on Azure. Mentor junior engineers, implement CI/CD and infrastructure-as-code, ensure security and performance, and partner with stakeholders to deliver production-ready data for analytics and automation.

Lead operational management and support of the enterprise data platform (primarily Snowflake), ensuring stability, scalability, observability, incident management, and migration from SQL Server. Manage data operations team, establish runbooks/SLAs, coordinate cross-functional readiness, drive continuous improvement, and ensure governance, compliance, and performance of data pipelines and platform services.

Take end-to-end ownership of backend features and SaaS services in a microservices architecture. Design, implement, deploy, and operate scalable, reliable Node.js services. Work with Redis Streams, MongoDB, Kubernetes, and ensure test coverage, performance tuning, and collaboration with cross-functional teams.

Lead global data and AI engineering to deliver scalable, secure, and compliant data platforms and MLOps capabilities. Own strategy, architecture, operations, SRE practices, observability, and reusable self-service components to support analytics, AI, and enterprise programs.

Design and analyze experiments and causal studies, build retention measurement and predictive models, develop scalable PySpark/SQL data pipelines, create dashboards, and partner with product and growth teams to improve user engagement and retention.

Lead technical strategy and hands-on implementation for Faire's data platform. Architect and scale ETL/ELT, streaming and batch pipelines, data warehousing, orchestration, monitoring, cost optimization, security, and governance. Mentor teams, prioritize platform roadmaps, and partner with product, analytics, and data science to enable self-serve data capabilities across the company.

Design and lead enterprise graph database and semantic data architectures, define ontologies and knowledge graph structures, integrate graph systems with cloud platforms, support LLM and AI use cases, run discovery workshops, document architecture, and mentor engineering teams.

Design and lead scalable enterprise data architectures using PostgreSQL and graph databases. Define logical and physical data models, optimize performance, modernize databases, integrate relational and graph systems, support AI/analytics platforms, produce governance documentation, and guide engineering teams through implementation.

Design end-to-end cloud-native AI and data platform architectures enabling Digital Twin and Knowledge Graph solutions. Lead architecture discussions, define scalable platform patterns, collaborate with AI/data/infrastructure teams, evaluate emerging AI technologies, produce technical documentation, and support solution discovery and roadmap planning.

Own and drive the architecture and roadmap of ClickUp's data platform. Build scalable, reliable data pipelines and AI/ML infrastructure using AWS serverless, Snowflake, dbt, and Terraform. Lead cross-team technical initiatives, optimize cloud costs, establish engineering standards (observability, testing, CI/CD), mentor senior engineers, and influence org-wide architecture decisions.

Support enterprise data governance by maintaining metadata, glossaries, and data catalogs; document lineage and data definitions; assist data quality, classification, retention, and unstructured data governance; support governance tools, audits, training, and cross-team collaboration to improve data accessibility, quality, and compliance.

The Data Scientist 2 will engage in the full data science lifecycle, including data extraction, model development, and deployment to meet business needs.

The Clinical Data Scientist designs and executes data assessment frameworks, evaluates RWD fitness, and supports evidence generation across Sanofi's enterprise, ensuring optimal data usage and collaboration across teams.

As a Data Scientist II, you will build and deliver data science solutions, validate models, support teams, and communicate insights to stakeholders.

The role involves designing and validating data and AI architectures, collaborating with customers, and ensuring scalable, secure solutions are implemented in enterprise environments.

Lead design, development, testing, implementation and support of data and AI products. Translate business requirements, provide technical direction, mentor developers, build automation and frameworks, improve delivery processes, and perform data analysis, profiling and regression testing.

Leads donor database and fundraising systems management, data integrity, gift processing, integrations, reporting, segmentation, automation, compliance, and process improvement. Manages and coaches a Database Coordinator while partnering with fundraising, communications, finance, and global teams. Develops Power BI dashboards, analyzes donor and campaign data, oversees vendor relationships, maintains data quality, and translates complex information into actionable fundraising and organizational insights.

Designs, builds, and maintains scalable batch and real-time data pipelines supporting an IoT safety ecosystem. The role manages ETL/ELT processes, data lakes, warehouses, lakehouses, orchestration, monitoring, data quality, and observability. It partners with product, engineering, analytics, and data science teams to deliver reliable data services, productionize models, and shape long-term data platform architecture using AWS and modern infrastructure practices.

Lead data management for clinical trials including database setup, eCRF specification, validation/edit checks, testing, data review/reconciliation, SAE reconciliation, database lock/unlock, vendor data transfers, training, and DM documentation to meet timelines and quality standards.

Perform end-to-end data conversions for CityView implementations: map source-to-target data, develop reusable conversion scripts, troubleshoot issues, coordinate with customers and project teams, and deliver tested conversions to test and production environments while following CityView methodology and timelines.

Own end-to-end product analytics for the Pro team: build production-grade pipelines and dbt models, define north-star metrics, design A/B tests and causal inference frameworks, create dashboards and metric frameworks, embed AI tooling, and translate insights into product recommendations for leadership.

Own go-to-market strategy and adoption for Stripe's data products. Develop positioning, messaging, competitive intelligence, launch plans, demand programs, and sales enablement. Translate customer and market insights into roadmap recommendations and measurable KPIs while partnering cross-functionally to drive commercialization and growth.

Build and scale AI data and ML infrastructure: evaluation systems, fine-tuning pipelines, agent-first product surfaces, high-throughput data workflows, and integrations of new models into production.

The Data Scientist role involves developing and deploying machine learning models for fraud detection, transforming datasets into insights, and collaborating across teams. Responsibilities include building data pipelines and ensuring model performance.

Partner with customers to scope and deliver custom data requests, conduct Business Value Analyses, lead API integrations, build internal data tools and automations, produce executive-ready insights, and mentor analysts while collaborating cross-functionally to scale data solutions.