Top Data Engineer Jobs in Montreal

Build and maintain scalable ETL pipelines and databases to ingest, transform, reconcile, and deliver OTC derivatives data for regulatory, operational, and business reporting. Develop SQL objects, stored procedures, and automated reports; enforce data quality, governance, and security controls; participate in Agile delivery, CI/CD, and production support.

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.

Design, build, and maintain SparkSQL/PySpark data pipelines in the central data lake to ingest IoT, product, and unstructured data (video/audio). Produce reliable computed tables for analytics, model training, and dashboards; integrate external datasets; ensure high data quality and uptime; and collaborate with Data Science, ML, and cross-functional teams.

Design, build, and operate large-scale Spark/PySpark data pipelines and the enterprise data platform. Implement data integrations, transformations (Python/SQL), monitoring, and data quality. Build MCP servers and AI-enabled tooling, optimize performance, mentor engineers, and lead cross-functional data projects to enable analytics and automation.

Build and maintain Java-based backend and scalable data pipelines while migrating legacy ETL from on-prem (Teradata) to cloud-native platforms (Databricks, Snowflake). Collaborate with engineering and architecture teams on modernization, performance tuning, testing, deployment, and production support for enterprise-scale distributed data systems.

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 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.

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.

Design, build, and maintain Snowflake-based data pipelines using dbt and Airflow. Own data modeling (dimensional modeling, SCDs), ingestion (batch and event-driven), data governance, observability, and tooling so teams can access reliable, documented analytics-ready datasets. Collaborate with analysts to define metrics and resolve quality issues.

Design, build, and maintain scalable ETL/ELT data pipelines and data platforms (warehouses, lakes). Prepare and transform data for ML, deploy and industrialize models on cloud (Azure, Snowflake, Databricks), implement MLOps/DevOps practices (CI/CD, monitoring), collaborate with cross-functional teams, and document solutions for continuous improvement.

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.

Build and operate scalable data ingestion, transformation, and connector frameworks; design and maintain a knowledge-graph-based data fabric; normalize and vectorize enterprise data for LLM/AI workflows; implement governance, lineage, access controls, and secure APIs to serve ML/agent pipelines.

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

Lead design, development and delivery of secure, efficient data pipelines using Databricks, AWS, Snowflake, Python and PySpark. Drive best practices, mentor teammates, collaborate with analysts and architects, and prepare high-quality data for machine learning and generative AI workflows within an Agile product team.

Design, implement, and optimize resilient batch and streaming data pipelines and cloud infrastructure. Mentor engineers, integrate AI-driven automation for pipeline delivery, and collaborate with data science and product teams to ensure scalable, production-grade data products.

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

Build, own, and evolve Flinks' data and ML platform: BigQuery/dbt pipelines, Airflow ingestion, Kubeflow/Vertex training, model serving, governance, observability, and cross-team data contracts to support production ML and analytics at scale.

Design, build, and operate scalable ETL/ELT pipelines and data storage for B2B products. Ensure data quality, low-latency performance, CI/CD, testing, monitoring, and technical leadership across cloud-based analytics systems.

Design, develop, test, and deploy high-performance Apache Spark/Scala data processing applications and ETL pipelines on Cloudera (CDH). Optimize Spark and platform performance, build data pipelines using HDFS, Hive, Impala, HBase, and Kafka, ensure data integrity and security, collaborate with data scientists and analysts, and implement version control and CI/CD for deployments.

Design, develop, and maintain data engineering solutions across the SDLC using Python (primary) and Scala (secondary). Build distributed data pipelines on Hadoop/Spark ecosystems, extend data processing platforms (Spark SQL, Hive, Starburst), manage CI/CD, and deploy on Kubernetes/OpenShift. Collaborate with stakeholders in Agile teams and ensure maintainable, reusable code.

Build and maintain responsive Angular UI components, collaborate with UX and backend teams, implement REST APIs and Python backend scripts, integrate basic ML models into data workflows, and participate in the full SDLC within Agile teams while ensuring code quality and performance.

Senior Data Engineer responsible for designing and validating data solutions, consolidating disparate data sources, documenting functional specifications, reviewing data models, supporting production deployments, investigating data quality issues, and collaborating with stakeholders and technology leads to ensure data completeness and lineage.