Vast develops commercial space stations to support sustained human activity, research, and manufacturing in low-Earth orbit and beyond.
<div class="content-intro"><p>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.</p></div><p>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.</p> <p>This will be a <strong>full-time</strong>, <strong>exempt</strong> position located in our <strong>Long Beach</strong> location.</p> <p><strong>Responsibilities:</strong></p> <ul> <li>Design, architect, and implement scalable enterprise data infrastructure including data lakes, warehouses, and real-time streaming platforms</li> <li>Build and maintain robust data pipelines that feed internal AI/ML tools and enable advanced analytics across all departments</li> <li>Own end-to-end data architecture from ingestion through transformation to consumption, ensuring data quality, reliability, and security</li> <li>Integrate data from complex engineering systems (PLM/Teamcenter), manufacturing systems (MES/MOM), ERP (NetSuite), IoT/sensor networks and other enterprise systems</li> <li>Create innovative data solutions that enable AI/ML capabilities for engineering analysis, manufacturing optimization, and supply chain intelligence</li> <li>Establish data governance frameworks, standards, and best practices across the organization</li> <li>Implement MLOps infrastructure to support model training, deployment, and monitoring</li> <li>Build real-time data pipelines from shop floor systems, test equipment, and operational technology (OT) environments</li> <li>Collaborate with Engineering, Manufacturing, Supply Chain, and business teams to understand data requirements and deliver BI/AI-ready datasets</li> <li>Lead and mentor a high-performing data engineering team, establishing technical standards and fostering a culture of extreme ownership</li> <li>Evaluate and implement cutting-edge data technologies including cloud-native services, vector databases, and modern data stack tools</li> <li>Optimize data pipelines for performance, cost-efficiency, and scalability</li> <li>Implement monitoring, alerting, observability, and disaster recovery capabilities for mission-critical data systems</li> <li>Provide technical leadership and strategic guidance on data architecture to executive leadership</li> </ul> <p><strong>Minimum Qualifications:</strong></p> <ul> <li>Bachelor's degree in Computer Science, Data Engineering, Computer Engineering, or equivalent work experience</li> <li>8+ years of hands-on experience in data engineering, data architecture, or related fields</li> <li>3+ years of experience in a technical leadership role leading data engineering teams or initiatives</li> <li>Proven track record of building enterprise-scale data infrastructure and production data pipelines</li> <li>Expert-level proficiency in SQL and Python</li> <li>Deep hands-on experience with cloud data platforms (AWS, Azure, or GCP) and associated data services</li> <li>Strong experience with modern data processing frameworks (Apache Spark, Kafka, Airflow, or equivalent)</li> <li>Demonstrated experience with data warehousing technologies (Snowflake, Databricks, BigQuery, Redshift, or similar)</li> <li>Experience supporting AI/ML initiatives with production-grade data pipelines and infrastructure</li> </ul> <p><strong>Preferred Skills & Experience:</strong></p> <ul> <li>Experience in manufacturing, aerospace, defense, or hardware-intensive industries</li> <li>Background integrating data from PLM systems (Teamcenter, Windchill), ERP systems (NetSuite, SAP), and MES/manufacturing execution systems</li> <li>Hands-on experience with MLOps tools, feature stores, and machine learning data pipelines</li> <li>Knowledge of DevOps/DataOps practices including CI/CD, infrastructure as code (Terraform, CloudFormation), and containerization (Docker, Kubernetes)</li> <li>Experience with real-time streaming architectures and event-driven systems</li> <li>Familiarity with vector databases, knowledge graphs, and AI/LLM data architectures</li> <li>Understanding of dimensional modeling, data vault methodology, and modern data architecture patterns</li> <li>Contributions to open-source data engineering projects</li> <li>Experience with digital twin architectures or simulation data management</li> <li>Strong understanding of data security, compliance, and governance in regulated industries</li> <li>Excellent communication skills with the ability to translate complex technical concepts to non-technical stakeholders</li> <li>Proven ability to balance strategic vision with tactical execution in fast-paced startup environments</li> <li>Track record of extreme ownership—proactively identifying problems and driving solutions to completion</li> </ul> <p><strong>Additional Requirements:</strong></p> <ul> <li>Ability to travel up to 10% of the time to other Vast facilities or vendor sites</li> <li>Willingness to work extended hours or weekends to support critical mis