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# Data Solution Architect

- **Company:** Boeing Company
- **Location:** Everett, WA, United States
- **Experience:** Expert
- **Salary:** $125,800.0 - $170,200.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Data Analysis, Cloud Computing, Continuous Integration, Data Architecture, Extract Transform Load (ETL), Data Mining, Data Security, Data Warehousing, Database Applications, Database Design, Database Queries, Python (Programming Language), Standard Sql, SQL Databases, Unstructured Data, Cloud Platform System, HybridCloud, Gitlab, Git, Data Lakes, Core Data, Data Analytics, Api Design, Software Version Control, Data Pipelines
- **Published:** September 5, 2026
- **Apply:** https://www.careerjet.com/job/usdd58587927172e8ac8dfc6858f8ef405/eaa

## About the Role

5+ years of experience working in a Data Solution Architect role within a manufacturing or automotive environment
5+ years of experience with data analytics and integration
5+ years of experience of SQL knowledge
Data Modeling - Ability to translate business requirements into clear, scalable, and industry-standard data models that support analytics and operational needs
Preferred Qualifications (Desired Skills/Experience):
Bachelor's degree in a directly related field (such as technology, engineering, supply chain, or Data Science) or possess an equivalent combination of relevant education and experience
Experience communicating and presenting to senior leadership
Experience working with customers in a manufacturing environment
Experience working with:
SQL
Core foundational skill. The architect should be able to design tables for both analytics and applications, and optimize slow or complex queries
Python
Primary programming language for building APIs, ETL pipelines, and data-driven applications. Strong proficiency is essential
ETL (Extract, Transform, Load)
Fundamental to how our team moves and integrates data. The architect should be experienced in designing and maintaining robust ETL processes
Data Modeling
Ability to translate business requirements into clear, scalable, and industry-standard data models that support analytics and operational needs
Cloud Experience
Basic familiarity with at least one major cloud platform (e.g., AWS - preferred) is sufficient, with familiarity in core data and compute services
GitLab
Hands-on experience with Git-based version control and GitLab workflows (branching, merge requests, CI/CD) as part of their daily development practice
Conflict of Interest:
Successful candidate for this job must satisfy the company's Conflict of Interest (COI) assessment process.

## Description

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.
Boeing Commercial Airplanes (BCA) is seeking an Experienced Data Solution Architect to work in the Production AI & Digital Strategy team within the Manufacturing & Safety organization based in Everett, Washington on First Shift.
This role requires a highly skilled individual contributor who will lead and facilitate the development, integration, and execution of strategic business programs, plans and projects supporting AI-driven production initiatives.
Position Responsibilities:
You will be instrumental in leading cross-functional projects to design, develop, maintain and optimize internal company data architecture for complex databases / data warehouse required to operate the business.
Complete data modelling for acquisition and database implementation collaborating with different stakeholders.
Apply data extraction, transformation and loading techniques in order to connect large and complex data sets from a variety of sources.
Lead creation of data collection frameworks for structured and unstructured data and solves complex data problems to generate features required by data scientists.
Lead activities to develop and maintain complex infrastructure systems (e.g., data warehouses, data lakes) including data access APIs.
Analyze and manage complex data.
Guide other data and analytics professionals on data standards and practices while creating a culture of sharing, reuse, design for scale stability, and operational efficiency of data and analytics solutions.
Lead build of repeatable data pipelines across complex multi- and hybrid-cloud environments.
Leverage Artificial Intelligence, Automation & CI/CD extensively for scalability, repeatability, and reuse.


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