At Boeing, we innovate and collaborate to make the world a better place. We’re committed to fostering an environment for every teammate that’s welcoming, respectful and inclusive, with great opportunity for professional growth. Find your future with us.
The Boeing Company is looking for a highly experienced and detail-oriented Senior Data Solutions Architect to join the team in Seattle, WA; Everett, WA; Tukwila, WA; Renton, WA; Berkeley, MO; Hazelwood, MO; or North Charleston, SC.
The Data Solution Architect is a highly motivated individual with a strong passion for solving complex problems and challenges. They are driven and will have a passion for building large-scale software systems.

BASIC QUALIFICATIONS (REQUIRED SKILLS/EXPERIENCE):

• 5+ years of experience building platforms and data products
• 5+ years of experience working with data and data warehousing business solutions
• 3+ years of experience with cloud-platform technologies (AWS, Azure, GCP)
• Experience with data pipeline tools and Extract Transform Load (ETL) services
• Experience with the configuration of Application Programming Interfaces (APIs) for data ingestion
• Experience with Artificial Intelligence (AI) hardware and software integration
• Experience with C++, Python and Java

PREFERRED QUALIFICATIONS (DESIRED SKILLS/EXPERIENCE):

• A Bachelor’s of Science or higher from an accredited institution in Software Engineering, Computer Engineering or other technical degree
• Experience with DevOps/DevSecOps and CI/CD practices, methodologies and tooling
• Experience with Azure DevOps (ADO) or Team Foundation Server (TFS), GitLab, GIT, IIS, Windows Server
• Experience with PCF (Pivotal Cloud Foundry)/Tanzu and/or exposure to Amazon Web Services, Google Cloud Platform, or Microsoft Azure
• Experience with Cloud technologies and/or Cloud-native app development and microservices

• Designs, develops, maintains and optimizes internal company data architecture for complex databases/data warehouse required to operate the business
• Completes data modelling for acquisition and database implementation collaborating with different stakeholders
• Applies data extraction, transformation and loading techniques to connect large and complex data sets from a variety of sources
• Leads the creation of data collection frameworks for structured and unstructured data and solves complex data problems to generate features required by data scientists
• Leads activities to develop and maintain complex infrastructure systems (e.g., data warehouses, data lakes) including data access APIs
• Analyzes and manages complex data
• Guides other data and analytics professionals on data standards and practices
• Creates a culture of sharing, reuse, design for scale stability, and operational efficiency of data and analytics solutions
• Leads build of repeatable data pipelines across complex multi- and hybrid-cloud environments
• Leverages Automation extensively for scalability, repeatability, and reuse