Senior Data Architect
| Company | The Boeing Company |
|---|---|
| Location | Seattle, WA, USA, North Charleston, SC, USA, Hazelwood, MO, USA |
| Salary | $142800 – $207000 |
| Type | Full-Time |
| Degrees | |
| Experience Level | Senior |
Requirements
- 5+ years of experience delivering architecture & design solutions, supporting distributed data systems
- 5+ years of experience designing and implementing scalable computing infrastructure for data solutions, including cloud architectures (AWS, Azure, Google Cloud)
- 5+ years of experience with advanced data modeling techniques and both relational and NoSQL databases (e.g., SQL Server, Oracle, Teradata, MongoDB)
- 5+ years of experience with data governance frameworks and compliance standards relevant to data management
- 5+ years of experience with Artificial Intelligence (AI) and Machine Learning (ML) technologies, including the ability to integrate AI-driven insights into data architecture and analytics processes
Responsibilities
- Lead activities to define requirements, design and verify robust architecture, data and information management systems and components
- Lead the identification of design constraints and ensures architecture conforms to requirements
- Incorporate architecture functions into software development lifecycle
- Lead the development and configuration management of architecture views and models
- Assess of feasibility of architecture solutions and alternatives
- Perform trade-off analyses
- Evaluate products to assess suitability for integration into delivery system environments
- Draft data and information management products and service standards
- Assess impact of architectural decisions to product lifecycle
- Develop architecture and data/information management standards and strategies
- Coach and mentor others
Preferred Qualifications
- Experience with headless data architectures and APIs, enabling flexible data delivery and integration across various platforms and applications
- Experience with semantic web technologies, including RDF (Resource Description Framework), OWL (Web Ontology Language), and SPARQL, to enhance data interoperability and knowledge representation
- Experience leading data visualization initiatives, including the design and implementation of interactive dashboards and reporting solutions that drive business insights
- Experience with data management best practices, including data governance, data quality, and data lifecycle management, to ensure the integrity and usability of data assets
- Experience with DataOps methodologies to streamline data workflows, enhance collaboration between data teams, and improve the speed and quality of data delivery
- Experience with data cataloging and metadata management tools to facilitate data discovery, lineage tracking, and data stewardship
- Experience with real-time data processing frameworks (e.g., Apache Kafka, Apache Flink) to support streaming data applications and analytics