Top Data Jobs in Toronto

Design and optimize scalable data pipelines, develop reusable frameworks, troubleshoot production issues, and enforce data engineering standards while collaborating with stakeholders.

The Data Engineer will design, develop, and maintain data pipelines, transform data, and support analytics for investment and client reporting in a cloud environment.

As a Data Analyst, you will support data migration initiatives by analyzing data structures, mapping source to target systems, and collaborating with stakeholders to document requirements and findings.

The Senior Data Engineer will design and maintain scalable data pipelines, collaborate with stakeholders, and ensure data governance and quality. Responsibilities include project ownership, mentoring juniors, and implementing data solutions across platforms.

Lead and mentor a large team of software engineers, manage complex projects, and drive software development strategy while ensuring high-quality and innovative solutions.

The Data Operations Specialist will manage data operations, ensuring quality data services and compliance, while optimizing data workflows and conducting audits.

The role involves leading projects in AEC data modeling and machine learning, mentoring junior engineers, and collaborating to enhance design workflows.

The Senior Data Software Engineer will design scalable data pipelines, develop backend services, and ensure data quality for AI-powered personalization. Responsibilities include working with diverse teams to translate business needs into robust data systems, ensuring accuracy, reliability, and performance optimization in production environments.

As a Photonics Data Analysis Engineer, you will develop software for analyzing and measuring photonic devices, requiring advanced mathematical skills and strong programming expertise, particularly in Python and data visualization.

The Lead Data Engineer will design and enhance data pipelines and infrastructure for data-driven decisions, mentor engineers, and establish data governance.

Design and maintain scalable ELT/ETL pipelines on GCP, build and evaluate predictive ML and NLP models (including LLM prompt engineering), implement XAI for interpretability, perform EDA and automation, and document governance and compliance to support enterprise fraud detection and SIU stakeholders.

Lead a team of data engineers and analysts, define the data engineering roadmap, oversee data infrastructure, ensure analytics delivery, and establish data governance standards.

Lead design and validation of advanced analytics and statistical methodologies, manage the Data Science team, ensure accuracy and rigor of models, integrate diverse data sources, support automation, produce actionable reports, and collaborate with Product, Technology and Operations stakeholders.

The Senior Data Scientist supports targeted marketing campaigns by analyzing data, developing insights, measuring performance, and mentoring team members with a focus on machine learning and statistical rigor.

Design and deliver statistical and causal models, experimental test designs, and predictive analytics to optimize loyalty, customer engagement, and marketing program performance. Collaborate cross-functionally to generate insights, validate results, and contribute to advanced analytics strategy.

As a Senior Engineering Manager in Data Engineering, you'll lead a team to build a Data Platform, improve engineering practices, and ensure project delivery through effective collaboration and system architecture design.

Build and maintain end-to-end ELT pipelines, design scalable data models, create APIs for data/ML serving, and collaborate with engineering, data, and business teams to deliver core data infrastructure.

Responsible for systems analysis, programming, and managing application development projects. It involves data processing management and consulting with users. Must ensure compliance with regulations while supporting business units and mentoring junior staff.

Partner with Product, Business, Data, and Engineering to scope and deliver end-to-end data science projects: analyze member behavior, evaluate experiments, build predictive models and recommendation systems, implement and measure solutions, and produce reusable features, datasets, monitoring, and stakeholder-facing insights.

The role involves building the data platform, overseeing architecture, improving performance and reliability, and collaborating with various teams. Responsibilities also include technical direction and mentoring other engineers.

The Senior Pyspark Data Engineer will manage large-scale data processing systems, conduct feasibility studies, provide user support, and develop security measures while acting as a subject matter expert in applications development.

Lead design and implementation of scalable Hadoop/Spark big data platforms and pipelines, optimize cluster performance, enforce data security/governance, mentor engineers, and integrate cloud-native services for analytics and near-real-time ingestion.

The Intermediate Data Engineer designs and builds scalable data solutions, manages data ingestion and pipelines, and supports BI initiatives. Responsibilities include collaborating with stakeholders, ensuring data integrity, and mentoring team members while adhering to best practices in data engineering.

The Senior Marketing Data Analyst will analyze global marketing data to provide strategic insights, optimize campaign performance, develop customer segmentation models, ensure data governance, and support reporting through BI tools.

The Senior Programmer Analyst leads application system development, ensuring quality coding and testing. They address complex data integration issues and mentor teams on ETL processes and compliance, focusing on operational excellence and continuous improvement.