Top Data Engineer Jobs in Montreal

The Senior Data Engineer will lead projects to enhance service delivery by modernizing data platforms and improving data-driven decisions through data integration and analysis.

The Staff ML Data Engineer will design and build data systems for AI products, focusing on multimodal data and ensuring efficient data workflows for machine learning research and production.

The Guidewire Data Engineer will design schemas in Snowflake, develop ETL processes, optimize SQL queries, and integrate Guidewire with data platforms.

Design, build, and optimize cloud-based data platform components: ingest and transform varied datasets, create metadata-driven pipelines and data APIs, support AI/ML infrastructure, implement monitoring and metrics, and improve data processes to enable analytics and operational systems.

As a Sr. Data Engineer, you'll design and manage data pipelines, enhance data quality, and leverage AI to streamline operations, driving the success of our AI growth platform for real estate.

As an Intermediate Data Engineer, you will develop data infrastructure and products, collaborate with diverse teams, and enhance technical quality across the data team.

Lead design and implementation of shared, reusable data models and a certified metrics layer. Standardize pipeline patterns, CI/CD, and governance; modernize orchestration and observability; partner with Data Science, Infrastructure, and Product to deliver reliable analytics pipelines and enable AI-native data development.

As a Senior Data Engineer, you will define and own data pipelines, design schemas, partner with scientists, and improve data infrastructure for Merge Labs' molecular optimization platform.

The Analytics Engineer will design data models, build pipelines, and ensure data quality to support AI evaluation and insights.

The Founding Data Engineer will manage the company's data models, ensure metric integrity, and work with various teams to deliver reliable metrics and reporting systems.

The Senior Data Developer will enhance the scheduling system, building pipelines for ML models, ensuring reliability, and facilitating improvements for operational decision-making.

The Senior Data Engineer will lead the data engineering architecture and roadmap, design scalable ELT pipelines, model data, ensure data quality, and maintain the cloud infrastructure, collaborating closely with data experts and engineering teams.

As a Data Engineer, you'll design and maintain data pipelines, model data for analytics, ensure data quality, and collaborate with teams to meet data needs.

The Data Engineer will build scalable data systems and analytics platforms, ensuring data quality and reliability for B2B products. Primary responsibilities include architecting high-scale systems, engineering pipelines, and optimizing data access and storage solutions, while collaborating with a cross-functional team.

Lead data engineering efforts to build and optimize ETL processes, ensuring reliable data for decision-making across business units. Collaborate with BI and Analytics teams to enhance data integrity and drive user growth.

Lead the design and implementation of scalable data engineering solutions, optimizing ETL processes, ensuring data quality, and collaborating with cross-functional teams.

As a Growth Data Engineer, you will build and manage marketing data and attribution systems, ensuring reliable data flow and accurate measurement of acquisition efforts. The role involves collaboration across product, marketing, and data teams with a focus on optimizing campaign performance.

The Founding Data Engineer will design and build OpenArt's core data platform, ensuring data reliability, consistency, and scalability to support leadership and product metrics.

The Staff Data Engineer will design and implement scalable data pipelines, mentor junior engineers, and enhance data system performance and architecture.

The Lead Data Engineer will design and build scalable data pipelines on Databricks, develop ETL/ELT pipelines with PySpark, and mentor engineering teams for data transformation and analytics.

Design and develop scalable data pipelines using PySpark and Databricks, focusing on data ingestion, transformation, validation, and performance optimization.

The Labs Data Science Full Stack Developer will analyze unstructured data, develop tools and reports, improve data governance, and collaborate with stakeholders to enhance decision-making at Morgan Stanley.

As a Data Engineer at LiveKit, you will manage the analytics infrastructure, develop scalable GCP-based data pipelines, and ensure effective data movement and transformation processes, while collaborating with the Analytics and engineering teams.

Design and deploy scalable data infrastructure and models, maintain CDC pipelines, build reporting tools and dashboards, write high-performance SQL, partner with product and engineering to enable enterprise-wide analytics and data-driven decision making.

Lead scalable data engineering efforts, build and optimize ETL processes, enhance data quality, and support analytics and BI teams.