Top Data Engineer Jobs in Vancouver

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 a Data Engineer, you will develop and manage data pipelines, ensuring reliable data ingestion and delivery while optimizing for simplicity and performance.

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

Lead design and delivery of Azure-based data platforms and Data Lakehouse architectures. Architect Microsoft Fabric reporting, build scalable ETL/ELT pipelines, optimize SQL/Power BI semantic models, enforce data governance (PII, multi-tenant, retention), migrate legacy systems, mentor engineers, and create AI-ready pipelines feeding embeddings, vector stores, and feature stores.

As a Data Engineer at Remarcable, you will build AWS Lakehouse infrastructure, ELT pipelines, and data models, ensuring data quality and driving AI/ML capabilities for the organization.

Design and maintain scalable batch and real-time data pipelines, build governed data models for a CDP, ensure data quality and security, support identity resolution and customer 360, mentor junior engineers, and collaborate with analytics and business stakeholders to deliver actionable customer insights.

Build, maintain, and optimize a Go-based petabyte-scale vehicle data processing framework; integrate it with Databricks/Spark; implement CI/CD and Kubernetes deployments; monitor and troubleshoot performance; collaborate with data producers/consumers; research new big-data technologies to improve platform scalability and reliability.

The AI-Native Data Engineer will build data pipelines, architect databases, design GCP infrastructure, and automate workflows for energy management using AI.

Design, build, and optimize cloud-native lakehouse pipelines and curated data products using Python and SQL. Own data modeling, performance tuning, observability, governance, and orchestration. Enable multi-tenant SaaS reporting, analytics, and AI-ready datasets; troubleshoot production issues; mentor engineers and drive platform architecture and reusable engineering patterns.

The Data Engineer will build and manage scalable data pipelines and databases, collaborate on architecture, and drive data systems towards real-time capabilities in a fast-paced, innovative environment.

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.

Design, build, and harden Workday's Spark- and Trino-based cloud data platform. Implement fault-tolerant architectures, self-healing mechanisms, observability (tracing, metrics, alerts), scalability and multi-tenant isolation, and develop data-processing algorithms for interactive querying and large-scale cube building.

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 and mentor a team of developers, oversee cloud product delivery, drive engineering practices, and ensure high-quality standards while contributing to cross-functional initiatives.

The Senior Data Platform Engineer will design and operate a unified data platform, ensuring reliable data flows and collaborating across teams to shape data strategy and architecture.

Own technical execution of customer data migrations: explore source systems, export data, author declarative version-controlled mappings, transform and validate data, run end-to-end migrations on internal platform, build reusable templates/validation, troubleshoot discrepancies, and document mapping and transformation logic for auditable production cutovers.

Own and evolve ClickHouse's Python connectors and SDKs; build integrations with orchestration and transformation tools; design AI/LLM connector patterns for RAG, vector search, and feature pipelines; engage with open-source community; collaborate across product and engineering to prioritize and ship production-grade data integrations.

The Software Engineer will build and extend the data ingestion pipeline, find audio data sources, and work with scientists to enhance datasets for AI models.

Lead design and implement a scalable Medallion lakehouse on GCS and Databricks. Build and govern ingestion and transformation pipelines (Astro/Airflow, PySpark, Delta Live Tables), apply domain-driven data modeling, manage Unity Catalog access and lineage, collaborate with analytics and vendors, and proactively surface risks with clear documentation.

As a Software Engineer, you will create tools and pipelines for AI development, manage data solutions for ML teams, and ensure high-quality code.

Build and operate a reliable data platform: monitor infrastructure and pipelines, automate platform tasks, manage IaC and CI/CD, support RBAC and governance, contribute to data pipelines and migration, document runbooks, and participate in on-call incident response while improving AI-assisted engineering workflows.

As a Full-Stack Engineer at Labelbox, you will develop and maintain AI tools, focusing on data training systems, intermediate user interfaces, scalable architectures, and work in a collaborative, fast-paced environment.

Lead architecture and performance improvements for data-intensive distributed systems. Optimize query plans, indexing, caching, and latency (P95/P99) while contributing to JVM backend services and ensuring scalability and reliability for customer-facing platforms.

The role involves designing scalable data pipelines for 3D, video, and sensor data, optimizing infrastructure, and productionizing ML models with researchers.

Lead architecture and long-term direction of a multi-petabyte data platform powering AI-driven advertising. Drive cross-team initiatives across data engineering, ML, and product; improve scalability, reliability, cost-efficiency, and operational excellence; mentor senior engineers and influence platform strategy and modernization.