Top Data Engineer Jobs in Vancouver

Design, build, and maintain scalable cloud data pipelines and architectures. Develop and optimize ETL/ELT workflows, manage data warehouses (primarily BigQuery), implement governance and security, collaborate with engineers and analytics teams, enable ML/AI use cases, and maintain documentation, lineage, and high-availability pipelines.

Build and maintain core financial backend systems (trading, ledger, billing), transaction processing, reconciliation, and portfolio state management. Design and scale real-time and batch data pipelines, architect APIs and backend services, ensure reliability and observability, and contribute to distributed system design (event-driven, microservices, streaming). Partner with ML teams as needed.

Design, build, and operate cloud-native, serverless ClickHouse database infrastructure. Develop and maintain Kubernetes operators, improve metrics pipelines, support data ingestion/transformation (Spark/Kafka), collaborate with core DB and data plane teams, and ensure scalable, highly available distributed systems with production on-call responsibilities.

Design, build, and deploy scalable, secure data solutions on-premise and in Azure. Collaborate with engineering, security, and ops to implement modern data practices (Databricks, Snowflake, Python, SQL), produce solution designs, support project delivery, and promote DevSecOps and cloud best practices.

Build and operate backend services for vehicle telemetry and control: design and deliver features in Go/Python/Rust, manage high-scale analytical stores and migrations, implement stream processing and tiered storage, ensure observability and production ownership, and collaborate across teams to support fleet-scale vehicle data systems.

Design and own end-to-end data quality systems for managed AI data studies: define rubrics, sampling plans, automated checks, launch gates, drift detection, dashboards, and calibration. Investigate integrity issues, run root-cause analysis, build automation in Python/SQL, and partner with Product, Engineering, and Operations to embed quality controls, train reviewers, and scale repeatable quality playbooks across programs.

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.

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.

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.

Senior Java Big Data Developer with 8+ years building applications on Cloudera/Hadoop ecosystems using Spark and MapReduce. Responsible for designing performant Java (1.8+) solutions, data analysis of large datasets, unit testing (JUnit), and collaborating with/managing global technology teams. Preferred skills include Unix/Python scripting and familiarity with Hive, Impala, YARN, and Kafka.

The role involves deep troubleshooting, root cause analysis, and architectural optimization in the Data and AI ecosystem to enhance platform reliability and supportability.

Design, build, and maintain scalable data systems and ETLs on GCP; connect production data to business systems; generate analytics and ML-driven insights for GTM teams; work cross-functionally and introduce modern tools (Airflow, DBT, Presto, Hightouch).

Lead architecture and implementation of agentic AI systems powering Zuma's platform. Rebuild onboarding and integration frameworks, implement analytics and observability for LLM performance, translate product needs into technical solutions, mentor engineers, establish engineering standards, and work directly with customers to enable scalable, production-grade AI experiences.

Perform L3 network troubleshooting and RCA on production enterprise networks, review telemetry/logs/configs, label and annotate network behaviors for ML training, and help define schemas and data pipelines to support AI-driven infrastructure.

As a Data Engineering Architect, lead the transformation of data engineering into a modern platform, oversee architecture and technical leadership, design scalable systems, ensure data quality and governance, and mentor teams for a data-driven culture.

Design and implement real-time MAC data-plane software for high-throughput satellite links. Build packet-processing pipelines, queue and buffer management, retransmission and loss recovery, and integrate with PHY, modem, FPGA, DMA, and SoC hardware. Optimize for low latency and high throughput using zero-copy, scatter-gather, lock-free structures, and hardware offload. Lead architecture through prototyping, hardware integration, performance qualification, and operational deployment while diagnosing timing and synchronization issues.

Design and implement automated data quality frameworks and tests for BigQuery-based pipelines. Collaborate with data engineers and product to define data contracts and quality gates, build observability and anomaly detection, validate complex ELT/ETL processes, and integrate data tests into CI/CD workflows. Drive improvements in documentation, governance, and pipeline reliability.

As a Senior Software Engineer, you'll design and build scalable market data systems, improve API architecture, and enhance overall system performance, contributing to Alpaca's infrastructure for trading financial assets.

Lead the design and development of a data platform, integrating data sources, driving architecture migration, and ensuring robust data governance and API development.

Lead optimization and scaling of Snowflake architecture, build resilient ELT/ETL and MLOps pipelines, implement data observability, automate workflows with AI-assisted tools, and design enterprise semantic models to support analytics and commercial data products.

Build and automate large-scale ML data pipelines and tooling for autonomous trucking. Improve dataset curation, deduplication, labeling, evaluation, and metrics infrastructure. Collaborate with robotics, autonomy, and infra teams to support continuous learning, deployment, and scalable AI infrastructure for Kodiak's fleet.

The Senior Data Engineer will scale and evolve the data platform, develop ETL/ELT pipelines, establish best practices, and optimize systems for performance while collaborating with various teams.

Design, build, and operate a cloud-native data platform and ML infrastructure at scale. Own end-to-end pipelines from CDC to feature stores, model training/serving, monitoring, and data product SLAs. Apply distributed systems and MLOps practices, leverage LLMs/agentic systems, and translate technical issues to business impact.

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.

Seeking Data Platform Engineers to design, build, and manage scalable data pipelines and analytic query engines while ensuring data integrity and performance optimization.