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Salary: USD 105,000 - 125,000 / annual
BETA Technologies is revolutionizing electric aviation and seeks a Data Platform Engineer to design, deploy, and operate the data and knowledge infrastructure powering the organization. This is a hands-on engineering role combining software and data engineering fundamentals with cloud-native architectures, graph databases, and API design to build robust, scalable production systems.
Key responsibilities include:
- Design, build, and operate scalable data platform services and frameworks that empower domain teams to manage data assets within enterprise architecture
- Implement data integration solutions creating a digital thread connecting information across the product lifecycle from design through manufacturing to field operations
- Build and maintain data storage systems including data lakes, warehouses, and graph databases to power advanced analytics and AI
- Create and extend enterprise data catalog capabilities documenting organizational data, its structure, and connections
- Develop performant data access layers using GraphQL and REST APIs
- Deploy, monitor, and manage production data systems on cloud infrastructure ensuring high availability, performance, and reliability
- Implement data quality and lineage solutions ensuring accuracy and traceability across diverse data types for aerospace compliance
- Build and maintain CI/CD pipelines, infrastructure as code, and automated deployment processes
- Partner with cross-functional teams on DataOps practices and data governance
- Contribute to collaborative team environment through code reviews, knowledge sharing, and constructive feedback
The ideal candidate is pragmatic and hands-on, thriving on solving real infrastructure and data challenges end-to-end from initial design through production operations, taking pride in building systems that make data more findable, accessible, and reusable across the enterprise.
Minimum Qualifications:
- 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 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 built data pipelines and data models that ingest and transform data from diverse sources to serve multiple consumers or use cases
- Built and maintained CI/CD pipelines, infrastructure as code, and containerized deployments (e.g., Docker, Kubernetes) for production systems
- Strong troubleshooting skills with ability to diagnose and resolve issues across the full stack from infrastructure through application layers
- Excellent communication skills with ability to translate technical concepts for diverse audiences
Desired Qualifications:
- 5+ years of experience building and operating production data platforms at scale
- Experience with semantic technologies including knowledge graphs, ontology design, and related standards (RDF, OWL, SPARQL, SHACL, RML/R2RML)
- Familiarity with AI-assisted development tools such as agentic coding assistants
- Experience with distributed computing frameworks (e.g., Spark) and/or event-driven and streaming architectures (e.g., Kafka, Kinesis)
- Hands-on experience with metadata management platforms and enterprise data catalogs
- Implemented data lineage and data quality solutions at scale
- Experience with monitoring, observability, and alerting for production data systems
- Experience working in regulated industries or with complex data governance frameworks
- Familiarity with aerospace or manufacturing data standards and regulations
- Knowledge of IoT protocols and time-series data management
