Top Data Jobs in Toronto

The Guidewire Data Engineer will design schemas in Snowflake, develop ETL processes, optimize SQL queries, and integrate Guidewire with data platforms.

The role involves designing and implementing scalable data models using Data Vault techniques on Azure. Responsibilities include collaborating with stakeholders, optimizing data vault models, ensuring data security, and documenting data processes.

Design, build, and maintain scalable data pipelines and tenant-aware APIs to ingest and transform data from ad platforms, order systems, and real-time events. Ensure reliability, observability, and maintainability across event-driven and batch architectures, implement authentication flows, optimize data workflows in a cloud-native environment, and collaborate with product, infrastructure, and data teams to onboard new sources.

Data Contributors will research startups, analyze global data for StartupBlink's Global Startup Ecosystem Index, and compile accurate information for publication.

Lead enterprise-wide AI adoption by translating technical AI concepts for non-technical stakeholders, curating education and communications, partnering with change management and L&D, triaging requests, and building a team to drive measurable AI adoption across the organization.

Design and optimize SQL Server solutions, manage data, automate processes with PowerShell, and integrate with external systems to enhance functionality.

Manage technical data for IP Routing hardware NPI programs: support NPI from data entry through factory implementation, maintain product data and Engineering Change Orders across the product lifecycle, and coordinate with engineering, supply chain, and manufacturing to ensure accurate PLM/PDM records and implementation.

Lead design and implementation of Jane's customer data infrastructure: own event collection, pipelines, CDP tooling, schema governance, identity resolution, and attribution. Work cross-functionally with marketing, BI, product, and engineering to set standards, evaluate tooling (e.g., RudderStack), ensure privacy-compliant instrumentation, and build reliable, consistent data delivery to the warehouse.

As a Backend Engineer on the Data team, you will design and maintain data pipelines and services, ensuring data quality and scalability while collaborating with cross-functional teams to meet data needs.

Lead strategic architecture for front-office investment technology and data solutions, advising on platform selection and implementation (Aladdin, Charles River, Bloomberg, etc.), guiding data architecture, governance and quality, managing small-to-medium implementation teams, and ensuring delivery across portfolio management, trading, and reporting domains.

Lead a distributed team of data scientists and engineers, focusing on data infrastructure and ML systems while collaborating with product and marketing teams.

Develop and maintain reliable, secure, high-throughput cloud data services. Collaborate with product and architecture teams to design cloud-native solutions, build and evolve APIs, improve processes, document and present solutions, mentor peers, and work with CI/CD pipelines and cloud databases to deliver scalable services used by millions.

Design and build scalable ETL data pipelines and RESTful APIs/microservices. Improve performance, monitor and troubleshoot data flows, ensure data security/compliance, write tests, and collaborate cross-functionally.

Lead delivery and operations for Wealth data and analytics platforms, ensuring governance, data quality, security, modernization (cloud and legacy), vendor coordination, financial oversight, and production readiness to support reporting, regulatory, and business insights.

Lead enterprise data governance and strategy for finance data. Develop and enforce policies, deploy governance technologies, ensure data privacy, quality, metadata, MDM and ontology design. Align data practices with business objectives, conduct audits, drive organizational change, partner with stakeholders, and build high-performing teams to manage risk and maximize data value.

Design, build, and maintain a robust data ecosystem and ETL pipelines to support digital campaigns, reporting, and analytics. Optimize data assets for performance and quality, partner with stakeholders to translate requirements into solutions, act as a data steward and subject-matter expert, and deliver iterative improvements within a Kanban continuous-delivery framework.

Build AI-native automation systems, developer tooling, and high-scale data ingestion for sportsbook odds and market feeds. Create AI workflows/agents that generate and validate code, maintain data feeds, automate debugging/testing/deployments, and monitor failures with automated remediation. Focus on internal automation, LLM orchestration, and distributed backend pipelines to accelerate the engineering team.

Design, build, test, and deploy production-grade data pipelines, APIs, and distributed PySpark workloads on Microsoft Fabric and Azure. Use Python, dbt, Airflow, and Docker to package and orchestrate workloads, implement data quality, observability, lineage, and governance (Purview), and collaborate with governance, analytics, and IT teams to deliver scalable, secure, production-ready data platform solutions.

Senior Data Analyst mines and analyzes prospect, client, and advisor data to generate insights that grow client acquisition and improve lead conversion. Responsibilities include requirements gathering, data extraction and analysis, KPI development, dashboarding and reporting automation, forecasting and plan support, triaging code/data issues, and collaborating with stakeholders to operationalize analytics-driven decisions.

Lead design and implementation of a scalable data platform handling petabytes of telematics and time-series data. Build and optimize streaming and batch pipelines, design storage solutions, implement observability and data lineage, manage HA infrastructure, and write maintainable Java/Python code while shaping long-term architectural strategy.

Lead investment data governance by designing and operating data quality controls, reconciling and troubleshooting investment system data, administering reference/security master and pricing data, managing vendors, supporting front-office/trading applications, and participating in system releases and MDM activities to ensure accurate, timely data for investment decision-making.

Lead design and implementation of scalable data models, ETL/ELT pipelines and migrations to Snowflake/Databricks. Optimize data workflows, ensure data quality and governance, support analytics reporting, and provide technical leadership to junior engineers while collaborating with stakeholders to deliver data-driven solutions.

The Senior Data Scientist will influence Wealthsimple's crypto experience by leveraging data analysis, problem-solving skills, and strong collaboration with cross-functional teams to shape product strategy and improve customer engagement and retention.

Lead and mentor a team of data analysts to build dashboards, reports, and advanced analytics. Partner with Core Data and cross-functional leaders (Finance, RevOps, CS, GTM) across NA and EMEA to define KPIs, execute an analytics roadmap, ensure data governance and quality, and apply predictive modeling to drive business decisions. Serve as the Director of Data's North America presence and champion scalable BI and data modeling best practices.

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