Boeing Vancouver
Aviation
DataEngineer
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Data Engineer at Boeing Vancouver. Skills: Data Engineering, AI, Analytics, Machine Learning. Support data science modeling efforts. Support problem-solving efforts”
Industry & Context.
Versatile problem-solver; Conceptual mind
Work onsite at Richmond location, Not sponsor visa, Not pose risk, Eligible for US export-controlled data
What They're Looking For.
Must Have
Minimum 3-year Cloud deployment experience, Minimum 3 years’ experience in relational and non-relational database technologies, Minimum 3-years’ experience supporting data science, AI/ML and analytics projects, Minimum 2-years of experience with Python, Legally able to work in Canada, Not pose a risk for safeguarding controlled goods, Eligible to handle US export-controlled data
Nice to Have
Experience working with Databricks, Experience working with Unity Catalog, Experience working with Databricks Genie, Technical degree/diploma in related field, Experience working with Large Language Models, Experience working with NLP technologies, Experience working with graph databases, Experience working with knowledge graphs, Experience with GraphQL, Experience with Cypher, Experience designing data quality monitoring solutions, Expertise in data modeling principles, Experience with development tools, Experience with deployment tools, Experience with version control tools, Experience with production-level Software Development, Experience with spec-driven development, Experience with DevOps technologies, Experience with CI/CD, Experience with Docker, Experience with cloud-deployed APIs, Experience with micro-services, Experience in pipeline software
What You'll Do.
Support data science modeling efforts
Support problem-solving efforts
Support sensor data ingestion
Support anomaly detection
Support predictive maintenance tooling
Propose data engineering solutions
Support modeling strategies
Support AI/ML systems
Support agentic systems
Design data ingestion pipelines
Build data ingestion pipelines
Support data ingestion pipelines
Design processing pipelines
Build processing pipelines
Support processing pipelines
Implement delta tables
Implement knowledge graphs
Implement MLOps pipelines
Maintain data quality
Monitor data integrity
Maintain data integrity
Monitor data consistency
Maintain data consistency
Monitor system health
Monitor scientific performance
Design scalable systems
Build scalable systems
Design reliable systems
Build reliable systems
Design high-performance systems
Build high-performance systems
Take part in CI/CD implementation
Take part in CI/CD support
Contribute to technical documentation
How You'll Work.
Team & Collaboration
Multi-disciplinary data science team; Aviation engineers; Data scientists
Full Job Description
Data Engineer **Company:** Boeing Vancouver Boeing Vancouver is seeking a **Data Engineer (AI & Analytics)**, reporting to the Senior Manager of AI & Analytics working out of the **Richmond, BC** office. This role will help Boeing transform our industry through the application and continuous improvement of advanced analytics and machine learning in the aviation domain. The position will be embedded in a multi-disciplinary data science team producing industry-leading insights, and will use their data management, software development and infrastructure skills to help build bigger, faster, and better cloud-based tools and pipelines. They will be broadly responsible for the design, implementation and support of data pipelines, including the data models, data contracts, and model features. Boeing Vancouver Data Engineers may support multiple products, capabilities or teams as needs arise and priorities dictate. This **Data Engineer** , embedded in the **Schedule Reliability & Intelligence **will primarily support the development of predictive maintenance services and sensor-based analytics tools in support of such products and services as Boeing Aircraft Health Monitoring, Insight Accelerator and Self-Service Analytics. Areas of practice will including anomaly detection, AI-assisted prognostics and the development of orchestrated agentic AI tools. A successful candidate will exhibit interest and proficiency in the handling of big, time-series data sets, unstructured text data, knowledge graphs, data mesh technology and the implementation of AI/ML Ops pipelines. This is a challenging role, requiring versatile problem-solver with keen conceptual mind, ontological thinking, an understanding of data science and valuable data features, as well as computational load and performance. They will work closely with aviation engineers and data scientists in a problem-solving role, helping bridge the gap from data into working data science models. Although primarily responsible for d
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