Top Data Jobs in Toronto

Lead development and maintenance of the core data platform: build performant pipelines, data warehousing, and ML infrastructure; partner with data scientists to produce production datasets; ensure data governance, quality, lineage, and accessibility; integrate cross-platform data sources; automate reporting and deliver stakeholder insights to enable data-driven decisions.

The Senior Data Developer will build and operate a CDC streaming platform, managing Kafka and Flink infrastructure, ensuring reliability, and creating CI/CD pipelines for data streaming applications.

The Senior Data Scientist provides analytical support for campaign execution, utilizing data insights and machine learning techniques to solve business problems, establish predictive models, and lead data-driven solutions.

As a Data Engineer, you will design and implement scalable data pipelines and solutions, collaborate with teams, and apply new technologies in an Agile environment.

The Data Engineer will design scalable data pipelines, manage data solutions, collaborate with teams, and ensure project delivery on time while applying new technologies.

As Data Privacy & Product Counsel, you will develop and execute privacy strategies, navigate laws like GDPR/CCPA, scale privacy programs, provide guidance on product innovation, and negotiate data protection terms.

Build and maintain integrations and data pipelines connecting client databases, APIs, and SaaS tools. Extract, clean, transform, and move messy real-world data to feed retrieval and agentic AI systems, apply security and privacy best practices, and document reproducible integrations.

Lead and manage project governance, tracking, reporting, and documentation for enterprise reference data initiatives. Coordinate across Operations, Technology, and stakeholders, maintain project plans, risks, actions, governance decks, and support smaller Data Operations projects while applying PM best practices and enabling AI/data-driven solutions.

As a Solutions Architect, you will lead technical decisions and design content data integration solutions, ensuring scalability, reliability, and alignment with business objectives. You will also guide cross-team collaboration and produce high-quality architecture documents.

Own and maintain data platform infrastructure: provision Snowflake via Terraform, build CI/CD for dbt, implement data quality and observability, extend the OpenMetadata catalog, create developer tooling and reproducible environments, and ensure secure, production-ready data pipelines.

The Analyst, Data Strategy supports the implementation of data strategies and governance by collaborating with teams to gather requirements, develop policies, and ensure data alignment with business goals, while also managing budgets and promoting a data-driven culture.

Design and build an enterprise data warehouse on BigQuery, implement ETL/streaming pipelines from source systems, establish modelling standards (raw, staging, curated, semantic), enforce CI/CD/testing/observability, manage data quality and cost, partner with finance and stakeholders for reporting, and lead the team technically toward an AI-ready data foundation.

Lead and scale a product-focused data science organization to build production ML systems for personalization, recommendation, experimentation, and causal inference. Define strategy, partner with Product and Engineering, own end-to-end ML lifecycle, mentor the team, and measure product impact through robust analytics and monitoring.

Perform descriptive and diagnostic analysis on claims data, design metrics and prototypes, query and prepare datasets (T-SQL/SQL/MySQL), extract/clean/reconcile data, and communicate findings to stakeholders to support business objectives.

Evaluate and label model-generated and human-written software engineering outputs for coding, debugging, and codebase-related tasks. Assess agent trajectories, prompt models for complex coding tasks, proofread and improve responses, and report quality and performance trends. Part-time contractor role contributing to model development.

Evaluate and label model-generated and human-written code outputs, debug and assess code/agent trajectories, prompt models for complex data science tasks, review visualizations, and report quality trends to improve model behavior.

Design, build, and maintain ETL pipelines and data infrastructure using Python, SQL, PySpark, and Microsoft Fabric. Collaborate with analytics and data science partners to translate requirements, optimize queries, resolve data issues, and support scalable data workflows and system architecture for omnichannel analytics.

Lead development and scaling of machine learning and deep learning solutions using big data to generate business insights and improve customer experience. Design predictive models, perform large-scale data analysis and data wrangling, evaluate AI/ML feasibility, and collaborate with product and analytics teams to operationalize models. Provide technical consulting, influence stakeholders, and apply risk and ethical frameworks while independently handling non-routine problems and broader analytics responsibilities across business units.

Design, build, and maintain scalable data pipelines and architectures supporting analytics, AI, and ML. Implement dbt models, orchestrate workflows with Airflow (MWAA), develop Snowflake-based data warehouses, write Snowflake SQL and Python/Shell pipelines, create Power BI reports, and support AWS-native production deployments while following global data engineering standards.

The role involves designing, developing, and optimizing big data solutions using PySpark, mentoring junior engineers, and leveraging AI tools to enhance development productivity.

Lead data stewardship for TDS Governance & Control, ensuring data governance, data quality, metadata, retention, and risk controls. Support business and tech stakeholders on assessments, regulatory and audit activities, escalation of data risks, and provide SME guidance on data controls and executive reporting.

Support stakeholders by profiling, mapping, and validating financial reconciliation datasets. Build complex SQL queries and Python workflows, and use Snowflake and Databricks to design, transform, and manage large-scale finance data for reporting, reconciliation, and analytics. Ensure data quality, perform root-cause analysis, and support governance and documentation.

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.

The VP, Head of Policy & Data Operations manages data governance and operations for proxy voting policies, ensuring data integrity and operational excellence while collaborating across teams to optimize processes and manage risks.

Lead and influence teams in data engineering projects, focusing on data infrastructure, analytics, performance, and security while mentoring and providing technical guidance.