Top Data Jobs in Toronto

The Senior Consultant will lead the adoption of data governance in the Global WAM segment by implementing frameworks, facilitating stakeholder engagement, and overseeing data quality initiatives.

Use legal training to create and evaluate AI training data and relevance evaluations. Perform legal research and analysis, provide actionable feedback, support senior team members, present to stakeholders, and advocate for Responsible AI.

Lead analytics and operational insights for Customer Operations: define core metrics, build dashboards and forecasts, model churn/renewal risk, enable self-serve reporting, implement AI-enabled automation, and partner cross-functionally to drive retention, expansion, and support efficiency.

Support vehicle profitability analysis by developing automated COP/CMP-I models, dashboards, and forecasts using Power BI, Excel, and data techniques (regression, scenario modeling). Translate analytics into pricing and incentive insights, partner with IT to improve data quality, and drive process automation and forecasting for budgeting and strategic initiatives.

As a Data Architect, lead data architecture initiatives aligned with business strategies, design scalable solutions, and mentor architects. Champion modern practices and collaborate on strategic direction for complex data ecosystems in a regulated environment.

Design, build, and maintain scalable data platforms and pipelines using Azure Fabric, Databricks, and Snowflake. Optimize ETL/ELT workflows for reliability and performance, collaborate with analysts and scientists, ensure data security and compliance, and recommend improvements to data quality and analytics.

Lead strategic data evolution for Fund Administration clients, building dashboards, managing stakeholders, and translating business needs into actionable insights.

Lead full-cycle enterprise sales for data and intelligence consulting: originate pipeline, run discovery, manage complex multi-stakeholder deals, create SOWs with delivery teams, co-sell with partners, and meet revenue targets while leveraging AI tools.

The Data Governance Intern will assist in developing enterprise data catalogs, documenting data elements, and supporting data quality efforts using SQL and Python.

The Staff Data Engineer will design and build new data pipelines, improve data reliability, and collaborate with teams to deliver scalable solutions, while shaping the future of data engineering at CookUnity.

Responsible for bridging enterprise data with AI capabilities, translating business challenges into operational solutions, and driving complex sales deals by connecting technical solutions to business value.

The Senior Data Engineer will build and maintain the data platform, develop data pipelines, improve observability, and collaborate with teams in a cloud-based data environment.

The Senior Data Analytics Engineer designs and builds scalable data platforms, maintains ETL pipelines, optimizes SQL Server environments, and develops reporting dashboards to support data-driven decision-making.

The role involves developing predictive models and machine learning algorithms, analyzing data, and collaborating with teams to create data-driven strategies and solutions.

The Data Reporting Lead Analyst will analyze project data, develop reports and dashboards, ensure data integrity, and support PMO decision-making processes.

As a Senior Software Engineer, you will develop and maintain software for healthcare applications, utilizing big data technologies and programming languages, ensuring high-quality code and system performance.

The Data Scientist will design and maintain predictive models for customer growth, collaborating with various teams to ensure actionable insights and model performance.

The Lead Data Engineer will architect and develop reporting solutions, integrate AI, analyze complex datasets, and mentor team members to enhance data-driven decision-making.

The Applied AI Specialist will design and maintain data pipelines for ML, prepare datasets, collaborate with AI engineers, and ensure data reliability for AI applications.

Lead and coordinate client legacy data integration into TELUS Health systems. Oversee conversion tasks, ensure data quality, run workshops, identify gaps, propose process changes, escalate issues, prioritize conversion work, and report progress and risks to project management.

Senior data analyst/programmer using SAS or R to analyze commercial claims and EHR real-world data. Create longitudinal cohorts, derive baseline/outcome variables, assess data quality, apply epidemiologic study designs and statistical methods (regression, survival), review protocols/SAPs, and program TFLs. Familiarity with OMOP CDM and OHDSI tools is a plus; prior pharmaceutical experience preferred.

Lead enterprise data architecture and cloud data platform strategy (Snowflake, Databricks). Design integrations, APIs, ETL/ELT and streaming pipelines (Kafka, Flink, Spark). Establish data modeling, governance, quality, observability, and embedding/vector DB infrastructure; support implementations, client engagements, and LLM/RAG-informed retrieval and lineage requirements.

Lead AI engineering on the Data Platform: build Databricks Apps deployment paths, construct an AI layer over the Medallion Architecture and semantic layer, enable LLM/NLP systems and agentic workflows, embed AI tooling in the developer lifecycle, enforce guardrails for production safety, define metadata/modeling patterns, and mentor engineers to accelerate AI adoption.

Lead and scale Scribd's Data & Analytics organization across Product Analytics, Data Science, and Analytics Engineering. Build operating model, data governance, experimentation frameworks, AI-native workflows, and infrastructure to accelerate insight delivery. Develop director-level leaders, recruit talent, and embed data-driven decision-making at the executive level to drive growth, retention, and portfolio-wide strategy.

Supervise vault and data I/O technicians, enforce best practices, manage scheduling and training, coordinate project storage and LTO archiving/shipping, track digital records, support production departments, assist client troubleshooting, and liaise with engineering and production to adapt workflows.