Top Data Jobs in Toronto

The Lead Data Engineering Developer leads the design and development of data solutions, focuses on data quality, implements complex data pipelines, and mentors juniors.

The Senior Data Strategist will manage customer data governance, define strategies, and collaborate across departments to improve data quality and usability.

Lead Full Stack Data Engineer responsible for architecting, developing, and optimizing data solutions, mentoring teams, and driving AI integration in data processes.

Develop and maintain full-stack applications for Fixed Income trading and risk management, collaborating with traders and analysts for innovative solutions.

The Full Stack Data Engineer will design and implement scalable data solutions, optimize data pipelines, and leverage AI tools to enhance productivity. Collaboration with teams and engagement with data stakeholders is key.

The Business Intelligence Developer will create dashboards, optimize SQL pipelines, and provide data-driven insights for business decision-making using BI tools like Tableau and Google BigQuery.

The Senior Data Analyst will analyze player behavior, create dashboards, guide product growth with insights, and collaborate on A/B testing at Rovio.

The Data Scientist 2 will engage in the full data science lifecycle, including data extraction, model development, and deployment to meet business needs.

As a Data Annotation Specialist, you will break down engineering tasks for AI models, evaluate their responses, and ensure outputs are accurate through labeling and proofreading.

As a Data Engineer, you'll design, build, and maintain data pipelines, ensure data quality, and collaborate with stakeholders to deliver data solutions.

Lead and operate TD Securities' data platform, providing hands-on technical guidance to solution engineers. Design, implement and monitor cloud-native infrastructure, ensure platform stability, optimize costs, drive CI/CD and observability, liaise with stakeholders, and lead complex projects delivering data ingestion-to-consumption capabilities on Azure/Databricks/Kubernetes environments.

Develop analytics solutions and dashboards using Python in AWS, apply accounting knowledge to interpret financial results, analyze complex data to uncover trends, present insights to decision makers, recommend process and data-quality improvements, and support continuous improvement of reporting and data tools.

As a Data Engineer, you will design and implement data processes, governance, and optimize data infrastructure, facilitating data-driven decisions at Gore Mutual.

Lead and execute enterprise-level audits of data governance, platforms and controls; advise senior stakeholders on risks, remediation, and data-driven insights; manage and develop audit teams, plans, and communications to strengthen governance and regulatory compliance.

Lead baseline and ad-hoc reporting, operationalize campaign measurement, partner with business stakeholders to structure analyses, execute queries to surface insights on engagement and purchase patterns, and enable data-driven product and distribution decisions while complying with privacy and security requirements.

Lead design, development, testing, and implementation of finance reporting, forecasting and analytics solutions. Build and support cross-platform data pipelines and integrations using Azure, Databricks, ADF, Python and RDBMS; liaise with finance stakeholders, vendors, and regulators; provide advisory and product-ownership responsibilities for finance modernization.

Design, develop and maintain data controls and governance for Financial Crime & Risk Management systems. Lead complex data initiatives, perform data profiling, root cause analysis, troubleshoot data pipelines, automate processes, integrate databases with analytics platforms, and collaborate globally to ensure data integrity for payments and transaction monitoring.

Lead and grow a Data Engineering team to modernize enterprise data platforms (Snowflake/Databricks), deliver secure scalable batch and real-time pipelines, enable DataOps/MLOps, establish CI/CD and IaC practices, monitor platform health, and drive strategic platform migrations and performance optimizations with cross-functional stakeholders.

Lead delivery and ongoing management of CRM, billing, lending, and data platforms for Transactional and Commercial Banking. Partner with product, frontline, and back-office teams to align platforms with business workflows, manage vendors and governance, embed data quality and privacy practices, drive adoption through training, and build a data and analytics team as the function scales.

Provide analytics support to business lines and finance through data analysis, automated workflows, BI reporting, advanced analytics and generative AI. Engage stakeholders, present findings to senior leaders, improve processes, and implement cloud-based data solutions.

Design, model and implement enterprise data integration and ETL solutions using Oracle Hyperion Planning, Essbase, Oracle BI and Oracle Data Integrator. Analyze and cleanse source data, build automated extraction/transform/load processes, scheduling, monitoring and error notification. Provide full life-cycle data conversion, reporting, and automated distribution for centralized financial planning and budgeting systems. Work with business and IT stakeholders to design resilient, multi-tier solutions aligned with Government of Ontario IT standards.

Design, implement and maintain data integration and data quality solutions using Informatica PowerCenter/PowerExchange/IDQ, Oracle databases, and Unix shell scripting on AIX/Linux.

Support data integration, quality, analysis, and visualization efforts. Collaborate with cross-functional teams, build dashboards and reports (Tableau/Excel), perform exploratory analysis, and support data engineering and modeling to deliver business insights and recommendations.

Design and build high-performance SQL and Python data pipelines across PostgreSQL, BigQuery, Snowflake, and MongoDB. Implement RisingWave streaming and Kafka architectures, orchestrate workflows with Airflow on GCP, enforce data quality, deploy CI/CD for pipelines, and mentor teammates while collaborating with business stakeholders.

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.