Top Data Jobs in Toronto

Lead and develop a team of analysts, manage analytics projects, establish methodologies, and enhance reporting and automation processes.

Design and operate distributed inference systems for LLMs, build large-scale data pipelines, and debug production issues while collaborating with researchers and ML engineers.

As a Senior Data Engineer, you'll build and manage scalable data platforms using AI tools to process high-volume data and support analytics. You'll own the data lifecycle, architect data models, and automate workflows, enhancing data accessibility for product and analytics teams.

Design, develop, and optimize scalable data solutions and data pipelines using Databricks, Python, SQL, and Azure. Collaborate across teams for data integration and quality assurance.

The Product Data Analyst will analyze operational data, develop analytics frameworks, create dashboards in Tableau, ensure data integrity, and collaborate across teams to enhance decision-making and reporting.

The Data Conversion Engineer will manage data migration processes from legacy systems to a modern platform, developing ETL processes and ensuring data quality and reliability.

The role involves building and scaling data infrastructure for multimodal AI systems, developing high-throughput data pipelines, and collaborating with ML researchers and product teams to enhance data systems.

The Data Scientist will develop data labeling strategies, optimize datasets for LLMs, analyze data quality, and collaborate with engineering on data processing pipelines.

The Senior Data Scientist will lead data science strategy, develop models for lead qualification, fraud detection, and underwriting, and collaborate with product and engineering to enhance financial products.

The Data Engineering Lead oversees data engineering operations, manages teams, ensures data integrity, and drives innovation in data management and governance.

The Data Engineer will design and manage data pipelines and architectures, ensuring data quality and security while collaborating with cross-functional teams for effective analytics and reporting.

The Senior Data Scientist will develop models and analyses for risk and revenue decisions, collaborating with various teams to optimize funding for eCommerce.

Design and deploy scalable data infrastructure and models, maintain CDC pipelines, build reporting tools and dashboards, write high-performance SQL, partner with product and engineering to enable enterprise-wide analytics and data-driven decision making.

The Data Analyst will analyze complex data to provide insights for Finance and Operations, build dashboards using Looker, and optimize data quality.

As a Staff Data Scientist, you will analyze large-scale broadband data, develop and validate ML models, and integrate solutions into Calix Cloud, collaborating with teams for enhanced network intelligence and subscriber experience.

Design, develop, and optimize data infrastructure, focusing on GCP, ETL/ELT workflows, and data governance, while collaborating with cross-functional teams.

As a Data Engineering Architect, lead the transformation of data engineering into a modern platform, oversee architecture and technical leadership, design scalable systems, ensure data quality and governance, and mentor teams for a data-driven culture.

The Analytics Engineer will design data models, build pipelines, and ensure data quality to support AI evaluation and insights.

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

The AI-Native Data Engineer will build data pipelines, architect databases, design GCP infrastructure, and automate workflows for energy management using AI.

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.

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.

Responsible for designing, building, and maintaining scalable data pipelines using Databricks. Optimize ETL/ELT processes and ensure data quality, governance, and security.

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

As a Forward Deployed Data Analyst, you will configure and implement data systems for clients, ensuring their analytics are accurate and actionable. You'll work with teams to refine metrics and improve data processes, ensuring value from day one.