Top Data Engineer Jobs in Ottawa

Seeking a Data Engineer with expertise in database design, AWS services, and data analysis to help solve business challenges.

As a Senior Data Engineer, you will design and implement scalable systems, build data pipelines, ensure data quality, and improve data processing workflows.

Design, build, and maintain data pipelines and infrastructure for data-driven decision-making. Collaborate with teams to ensure data accuracy and develop scalable data systems.

As a Senior Data Engineer, you will design and manage ETL pipelines, create data models, and ensure data quality for compliance efforts.

The role involves building and operating a data platform for managing crypto exchange data, collaborating with teams, and mentoring peers, focusing on high-quality and scalable solutions.

As a Data Engineer, you will set the technical direction for a streaming data processing engine, implement it, ensure best practices, and work with teams to prioritize tasks and improve processes.

As a Data Engineer at Afresh, you will develop data pipelines, improve integrations, and streamline data processing to combat food waste.

The Analytics Engineer will design data models, develop ETL pipelines, ensure data quality, and enhance reporting solutions for People Analytics.

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

As a Data Engineer at Nascent, you will identify novel data sources, develop pipelines, conduct exploratory analyses, and collaborate across teams to enhance trading strategies.

The Staff Data Engineer will design and implement data ingestion and transformation solutions on cloud platforms while providing technical leadership and support to product teams.

As a Staff Data Engineer, you will enhance and modernize data platform infrastructure, manage data processing platforms, and mentor junior engineers.

Lead the design and implementation of a modern data architecture, manage ETL pipelines, ensure data quality, and collaborate with cross-functional teams.

The Senior Data Engineer will design and implement data pipelines, maintain data warehouses, and collaborate with teams on best practices, while mentoring junior engineers.

The Senior Data Engineer will design, develop, and test software applications, focusing on APIs, SQL Server tools, and cloud technologies, while mentoring junior staff and improving performance.

As a Senior Data Engineer, you'll design and maintain data infrastructure, implement scalable data pipelines, and collaborate with teams to optimize data synchronization and processing.

Join the AI team to manage data collection for model training, enhance cloud infrastructure for ingestion pipelines, and collaborate on datasets.

As a Senior Data Engineer, you will design and develop scalable data pipelines, collaborate with teams on data projects, ensure data quality and security, and optimize CI/CD processes.

As a Senior Data Engineer II, you will enhance and maintain data pipelines for analytics and machine learning while collaborating with various teams at Life360.

As a Data Engineer II, you will build and maintain ETL pipelines, analyze requirements, and mentor junior colleagues while supporting customer implementations.

The Data Platform Developer will design and implement data pipelines and ETL processes, ensuring data accessibility and governance for analytics.

As a Staff Software Engineer on the Data Science team, you'll develop and scale data science tools and machine learning models for the company's marketing intelligence platform, ensuring reliability and performance in data-driven solutions.

As a Staff Software Engineer on the Data Science team at Northbeam, you'll design and implement data-driven solutions, scale data products, and develop machine learning models, directly impacting the company's core product.

As a Senior Software Engineer on the User Data team, you will build scalable micro-services and manage user profiles using Golang and various modern databases.

Lead the design and build data pipelines, process large datasets, collaborate with teams for data integration, and improve data quality and performance.