Staff Data Architect
Role details
Job location
Tech stack
Job 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
Requirements
- 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
Benefits & conditions
Base salary will vary depending on job-related knowledge, education, skills, experience, business needs, and market demand. Salary is just one component of our comprehensive compensation package. Full-time employees also receive company equity, as well as access to a full suite of compelling benefits and perks, including: 100% medical, dental, and vision coverage for employees and dependents, generous paid time off; up to 20+ days of vacation for exempt staff and up to 10+ days of vacation for non-exempt staff with the ability to cash-out unused vacation annually, paid parental leave, short and long-term disability insurance, life insurance, access to a 401(k) retirement plan, ClassPass credits, personalized mental healthcare through Spring Health, and other discounts and perks. We also take pride in offering exceptional food perks, with snacks, drip coffee & onsite barista, cold drinks, and dinner meals remaining free of charge, and lunch subsidized as part of Vast's ongoing commitment to providing high-quality meals for employees.