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# Staff Data Architect

- **Company:** Vast, Inc
- **Location:** Long Beach, CA, United States
- **Experience:** Experienced
- **Salary:** $155,800.0 - $221,160.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Airflow, Amazon Web Services, Systems Engineering, Microsoft Azure, BigQuery, Computer Engineering, Continuous Integration, Data as a Services, Data Architecture, Information Engineering, Data Governance, Data Infrastructure, Data Integration, Data Security, Data Systems, Data Vault Modeling, Data Warehousing, DevOps, Dimensional Modeling, Disaster Recovery, Graph Database, Python (Programming Language), Machine Learning, Netsuite, Operational Databases, Cloud Services, DataOps, SAP (Applications), Wireless Sensor Networks, SQL Databases, Data Streaming, Windchill, Digital Twin, Google Cloud, Enterprise Software Applications, Large Language Models, Snowflake, Apache Spark, Cloudformation, Event Driven Architecture, Containerization, Data Lakes, Kubernetes, Information Technology, Integration Frameworks, Apache Kafka, Data Management, Machine Learning Operations, Terraform, Data Pipelines, Serverless Computing, Docker, Amazon Redshift, Databricks, Teamcenter (Software)
- **Published:** May 19, 2026
- **Apply:** https://www.dice.com/job-detail/51e77e51-6e7e-43e9-961a-25b0f6ecadd4

## About the Role

* 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 Google Cloud Platform) 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, BigQuery, 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 (NetSuite, SAP), and MES/manufacturing execution systems
 * Hands-on experience with MLOps tools, feature stores, and machine learning data pipelines
 * Knowledge of DevOps/DataOps practices including CI/CD, infrastructure as code (Terraform, CloudFormation), 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 stakeholders
 * Proven ability to balance strategic vision with tactical execution in fast-paced startup environments
 * Track record of extreme ownership-proactively identifying problems and driving solutions to completion

Additional Requirements:

 * Ability to travel up to 10% of the time to other Vast facilities or vendor sites
 * Willingness to work extended hours or weekends to support critical mission milestones and production launches

## Description

* 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 (NetSuite), 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


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