Data Platform Engineer | Digital Operations

Data Platform Engineer | Digital Operations

At BETA Technologies, we apply our intellectual curiosity, passion for aviation, and commitment to sustainability toward a shared mission of revolutionizing electric aviation. Regardless of the position one holds, each team member brings their talent and desire to positively impact the environment and lives of others in a refreshing, vibrant, and inclusive culture.

We are seeking a Platform Engineer to join our Data and AI Platform team, bringing strong hands‑on engineering skills and a builder's mindset to help design, deploy, and operate the data and knowledge infrastructure that powers our organization. In this role, you will combine software and data engineering fundamentals with practical experience in cloud‑native architectures, graph databases, and API design to build robust, scalable production systems that enable rich data discovery, seamless integration and reliable access across diverse data sources.

You will work collaboratively with data scientists, other platform engineers and domain experts to evaluate, architect and implement the most appropriate data solutions, and then roll up your sleeves to build, deploy and maintain them in production. The ideal candidate is a pragmatic, hands‑on technologist who thrives on solving real infrastructure and data challenges end‑to‑end from initial design through production operations, and who takes pride in building systems that make data more findable, accessible and reusable across the enterprise.

• Design, build, and operate scalable data platform services and frameworks that empower domain teams to manage their data assets within a cohesive enterprise architecture
• Implement data integration solutions that create a digital thread connecting information across the entire product lifecycle from design through manufacturing to field operations
• Build and maintain data storage systems including data lakes, warehouses, and graph databases that make organizational data accessible and ready to power advanced analytics and AI
• Create and extend enterprise data catalog capabilities that document what data exists across organizational systems, how it is structured, and how it connects, enabling teams across the company to navigate the full data landscape
• Develop and expose performant data access layers using technologies such as GraphQL and REST APIs, providing intuitive interfaces to complex underlying data
• Deploy, monitor, and manage production data systems on cloud infrastructure, ensuring high availability, performance, and reliability
• Implement data quality and lineage solutions that ensure accuracy and traceability across diverse data types; essential for aerospace compliance and establishing a trusted foundation for analytics and AI
• Build and maintain CI/CD pipelines, infrastructure as code, and automated deployment processes that keep our data platform agile, reproducible, and production‑ready
• Partner with cross‑functional teams on Data Ops practices and data governance to keep data assets trusted, accessible, and well‑managed
• Actively contribute to a collaborative team environment through code reviews, knowledge sharing, and constructive feedback that continuously improves our data solutions and maintains high engineering standards

• Bachelor's degree in Computer Science, Information Systems, Data Science, or related technical field (or equivalent practical experience)
• 3+ years building and shipping data or platform infrastructure in production, with ownership of system availability, performance, and incident response
• Strong software engineering fundamentals including clean code practices, testing, and building maintainable systems
• Provisioned, configured, and operated cloud‑based data services in production (preferably on AWS)
• Built or maintained systems using graph databases (e.g., Neo4j, Amazon Neptune, Stardog) and designed graph data models
• Designed and built APIs that other teams or systems depend on, with working knowledge of GraphQL
• Proficiency with modern data engineering tools and languages (e.g., Python, SQL)
• Designed and…