Top Data Jobs in Toronto

The Director, People Business Partner will enhance organizational effectiveness, talent management, leadership support, and people strategies using AI and data to improve outcomes and performance.

The Senior Marketing Analytics Lead will oversee analytics projects, translate data into insights, influence marketing strategies, and mentor junior team members.

As a Product Manager, you'll lead product vision and strategy, utilizing customer insights and technology to create innovative solutions while collaborating with multiple teams.

Lead global portfolio marketing for Advisors & Transformation, defining positioning and go-to-market for AI-enabled consulting (including Agent Suite). Drive integrated campaigns, sales enablement, thought leadership, and data-driven insights to accelerate adoption, pipeline, and revenue growth while aligning product, consulting, and regional teams.

Lead digital transformation initiatives, enhance commercial strategy, manage technology portfolios, and drive operational excellence in marketing and sales.

Build, deploy, and maintain machine learning models on large-scale datasets. Extract, clean, and analyze numerical and textual data. Develop model pipelines, run experiments, optimize business strategies, and evaluate new data sources and technologies.

The Engineering Manager leads Data Engineering teams, developing scalable data solutions and collaborating with stakeholders to drive McCain's digital transformation.

Lead design and delivery of enterprise-scale AI/ML solutions for Ethoca, building and governing models (NLP, generative, multi-modal) to reduce chargebacks, improve dispute resolution, and scale production systems across cloud environments.

Lead development, deployment, and monitoring of end-to-end ML/DL/AI solutions. Responsibilities include data extraction, cleaning, modeling, evaluation, production deployment, documentation, and presenting results. Collaborate across teams, build prototypes and POCs, protect IP, and disseminate knowledge externally.

Design and maintain ETL pipelines and Databricks Gold-layer tables; develop semantic layers, data dictionaries, and documentation for AI-driven BI; build dashboards and analyses to surface marketing and sales KPIs; perform ad-hoc deep dives; translate stakeholder requirements into scalable, analytics-ready data models; enable self-serve reporting and agentic AI workflows.

Lead a small team and contribute hands-on to design, develop, deploy, and iterate AML and crypto risk detection machine learning models. Own technical roadmap, collaborate with Product and Engineering, ensure model quality, explainability, documentation, and governance, and drive production performance and outcomes across the model lifecycle.

The DCIM Administrator manages data center operations by overseeing Nlyte workflows, ensuring accuracy in asset management, and driving continuous improvement in process and data integrity.

Lead client-facing data solutioning and pre-sales within Consumer verticals, design and translate architectures into delivery, maintain ~50% billable involvement, drive pipeline growth and close complex data opportunities while ensuring information security and privacy compliance.

Lead a team of senior product managers owning data ingestion, normalization, event processing, workflows, third-party integrations, and data governance. Define unified roadmap, partner closely with engineering, manage vendor relationships, launch integrations, and represent platform needs to Sales, Partnerships, and Customer Experience while prioritizing customer outcomes.

CommBank is seeking Indigenous job seekers for various roles across its sectors, offering traineeships, internships, and direct employment opportunities with support from an Indigenous Careers team.

Serve as the functional expert for SAP financial data, ensuring data integrity and alignment with P&L/Balance Sheet. Support SAP BW-IP planning, Power BI and BW reporting, troubleshoot complex issues, optimize BW data models, and enable integrations with modern data platforms like Databricks and OneStream.

The Data Engineer will develop and maintain data pipelines, ensure data quality, and collaborate with business teams to implement insightful data solutions.

Own, build, and optimize Spark-based production data pipelines and ML data lake on GCP Dataproc to support recommender systems. Collaborate with ML engineers, resolve performance bottlenecks, and deliver scalable, reliable data products for AI-driven personalization.

The Senior Data Engineer will design and maintain streaming data pipelines, develop analytical databases, and ensure data system reliability while collaborating with teams across the organization.

Lead design and build scalable data architectures, ETL pipelines, ingestion and data quality frameworks. Collaborate with cross-functional teams, enforce data governance, analyze data for insights, mentor junior engineers, and serve as the technical authority on data engineering best practices.

As Senior Product Manager, you'll manage the product roadmap, engaging with healthcare professionals and driving cross-functional execution in a high-growth tech environment.

Design, build, and maintain scalable data pipelines and storage (data lakes/warehouses). Integrate diverse sources, enforce data quality, security and compliance, optimize ETL/ELT, monitor pipelines, and mentor junior engineers while collaborating with data scientists, analysts, and stakeholders.

Design, build, and operate production ML systems that generate trusted signals for ranking, retrieval, recommendations, propensity/churn/LTV, and next-best-action decisioning. Define signal/data contracts, own feature and candidate generation through serving, experimentation, monitoring, and feedback loops, and evaluate long-term business impact, trust, fairness, and compliance. Partner across product, data, modeling, risk, and compliance and apply AI/agents to accelerate engineering and operations.

Lead the design and development of machine learning models, collaborating with teams to optimize solutions and mentor junior members while ensuring technical excellence.

Design and maintain data architecture and pipelines to support compliance and risk teams. Build and optimize data models, standardize metrics, and create data dictionaries. Implement data quality, lineage monitoring, AI-driven agents for false-positive reduction and automation, and participate in on-call rotations to ensure SLAs are met.