Top Data Engineer Jobs in Vancouver

The Data Engineer II will design, build, and optimize systems for metadata processing on a massive scale, collaborating closely with various teams.

As a Data Engineer at Clover, you'll develop data pipelines, tools for analytics and machine learning, and work on data governance and ETL processes. Collaboration with various teams and external parties is essential to ensure data accessibility and improve healthcare outcomes.

The ML Data Engineer will develop and manage robust feature engineering ETL pipelines for machine learning applications. Responsibilities include optimizing low-latency data pipelines, supporting the ML lifecycle, and ensuring compliance and data governance. Close collaboration with data scientists and other teams is essential to align data efforts with business needs.

As a Data Engineer, you will manage the data migration lifecycle by evaluating source systems, designing transformation rules, building ETL pipelines, and ensuring data quality. You will collaborate with business data owners and technical teams to facilitate secure data transfers and maintain documentation for auditability. Strong experience in data cleansing and validation is key to ensuring successful migrations.

Lead the design and development of data architecture, focusing on data modeling, integration, and analytics for Scribd's data strategy.

The Data Engineer I will maintain data models, ensure data consistency, collaborate with teams for KPI reporting, and improve data stack efficiency.

The Senior Data Engineer will develop scalable systems and infrastructure, enhancing data handling processes, and collaborating with technical teams.

The Senior Data Engineer designs and maintains cloud-based data solutions, optimizing data pipelines, ensuring compliance, and supporting business intelligence through data processing and reporting.

Samsung Research in Vancouver seeks a Senior Data Engineer to design and build scalable data architectures for large-scale data from Samsung’s cloud services and mobile devices. Responsibilities include improving data pipelines, implementing cloud-based data solutions, and collaborating with cross-functional teams to promote a data-driven culture.

As a Data Engineer II, you will optimize data architecture, develop scalable data pipelines, collaborate with analytics teams, ensure data quality, and design data integrations. You'll utilize various cloud services, write unit tests, and document processes while supporting real-time data integrations and effectively communicating with stakeholders.

Build and maintain a scalable AI data platform, collaborating with teams to ensure optimal data lifecycle management and infrastructure for machine learning applications.

As a Senior Analytics Engineer, you will develop complex SQL transformations, design data model structures, and enhance business logic to unify analyses across teams. You'll be a technical owner for data domains and collaborate with cross-functional partners, applying data modeling expertise to support decision-making processes.

As a Senior Data Engineer, you will lead the development of data pipelines and infrastructure to support Blackpoint Cyber's AI products. Responsibilities include optimizing ETL processes, implementing data models, monitoring performance, and collaborating with cross-functional teams to enhance cybersecurity measures.

As a Staff Data Engineer, you will design and optimize data pipelines, enhance ingestion architectures, and collaborate with enterprise customers and platform teams.

The Senior Data Engineer will handle data engineering activities like ingestion, modelling, and governance, and improve data pipelines for large-scale data. The role involves collaborating with various teams to define solutions and mentoring team members on best practices in data processing.

Design and develop data models in Snowflake, implement ETL processes, and support Guidewire Claims workflows with SQL querying and cloud integration.

As a Senior Data Migration Engineer, you will oversee data migration to GCP, analyze data structures, design strategies, ensure data integrity, and support stakeholders.