Data Architect

Position: Staff Data Architect
At Vast, our mission is to contribute to a future where billions of people are living and thriving in space. Vast is developing next-generation space stations to ensure a continuous human presence in space for America and its allies, enabling advanced microgravity research and manufacturing, and unlocking a new space economy for government, corporate, and private customers. Using an incremental, hardware-rich and low-cost approach, Vast is rapidly developing its multi-module Haven Station.

Haven Demo's 2025 success made Vast the only operational commercial space station company to fly and operate its own spacecraft. Next, Haven-1 is expected to become the world's first commercial space station when it launches, followed by additional Haven modules to enable permanent human presence by 2030. Our team is all-in, committed to executing our mission safely and on time.

If you want to work with the most talented people on Earth furthering space exploration for humanity, come join us.

Vast is looking for a Staff Data Architect, reporting to the Senior Director of Information Systems, to support the development of the data infrastructure and AI-driven capabilities that will be required for the design and build of artificial-gravity human-rated space stations.

This will be a full-time, exempt position located in our Long Beach location.

Responsibilities:

• Design, architect, and implement scalable enterprise data infrastructure including data lakes, warehouses, and real-time streaming platforms
• Build and maintain robust data pipelines that feed internal AI/ML tools and enable advanced analytics across all departments
• Own end-to-end data architecture from ingestion through transformation to consumption, ensuring data quality, reliability, and security
• Integrate data from complex engineering systems (PLM/Teamcenter), manufacturing systems (MES/MOM), ERP (Net Suite), IoT/sensor networks and other enterprise systems
• Create innovative data solutions that enable AI/ML capabilities for engineering analysis, manufacturing optimization, and supply chain intelligence
• Establish data governance frameworks, standards, and best practices across the organization
• Implement MLOps infrastructure to support model training, deployment, and monitoring
• Build real-time data pipelines from shop floor systems, test equipment, and operational technology (OT) environments
• Collaborate with Engineering, Manufacturing, Supply Chain, and business teams to understand data requirements and deliver BI/AI-ready datasets
• Lead and mentor a high-performing data engineering team, establishing technical standards and fostering a culture of extreme ownership
• Evaluate and implement cutting-edge data technologies including cloud-native services, vector databases, and modern data stack tools
• Optimize data pipelines for performance, cost-efficiency, and scalability
• Implement monitoring, alerting, observability, and disaster recovery capabilities for mission-critical data systems
• Provide technical leadership and strategic guidance on data architecture to executive leadership

Minimum Qualifications:

• Bachelor's degree in Computer Science, Data Engineering, Computer Engineering, or equivalent work experience
• 8+ years of hands-on experience in data engineering, data architecture, or related fields
• 3+ years of experience in a technical leadership role leading data engineering teams or initiatives
• Proven track record of building enterprise-scale data infrastructure and production data pipelines
• Expert-level proficiency in SQL and Python
• Deep hands-on experience with cloud data platforms (AWS, Azure, or GCP) and associated data services
• Strong experience with modern data processing frameworks (Apache Spark, Kafka, Airflow, or equivalent)
• Demonstrated experience with data warehousing technologies (Snowflake, Databricks, Big Query, Redshift, or similar)
• Experience supporting AI/ML initiatives with production-grade data pipelines and infrastructure

Preferred Skills & Experience:

• Experience in manufacturing, aerospace, defense, or hardware-intensive industries
• Background integrating data from PLM systems (Teamcenter, Windchill), ERP systems (Net Suite, SAP), and MES/manufacturing execution systems
• Hands-on experience with MLOps tools, feature stores, and machine learning data pipelines
• Knowledge of Dev Ops/Data Ops practices including CI/CD, infrastructure as code (Terraform, Cloud Formation), and containerization (Docker, Kubernetes)
• Experience with real-time streaming architectures and event-driven systems
• Familiarity with vector databases, knowledge graphs, and AI/LLM data architectures
• Understanding of dimensional modeling, data vault methodology, and modern data architecture patterns
• Contributions to open-source data engineering projects
• Experience with digital twin architectures or simulation data management
• Strong understanding of data security, compliance, and governance in regulated industries
• Excellent communication skills with the ability to translate complex technical concepts to non-technical…