Full-Stack Data Platform Engineer - Metrology SystemsOverviewWe are seeking an experienced Full-Stack Data Platform Engineer to design and build internal applications, data pipelines, and analytics tools that support metrology configuration, measurement data collection, and quality analysis across hardware programs and external manufacturing sites.
This role will own end-to-end architecture for metrology data workflows, including web applications, cloud-based data storage, serverless services, automated processing pipelines, dashboards, and AI-enabled analysis tools. The ideal candidate has strong experience building full-stack applications and cloud data platforms, with the ability to translate complex engineering and manufacturing requirements into scalable technical solutions.
Key Responsibilities- Design and build internal web applications using React and TypeScript to create and manage metrology configurations, including what is measured, where measurements occur, and how data is collected.
- Build and maintain cloud-hosted data platforms for measurement and quality data, including data lakes, automated folder structures, schema validation, and event-driven processing pipelines.
- Develop serverless backend services for configuration management, data ingestion, pass/fail evaluation against specification limits, and summary data aggregation.
- Create integration adapters that convert optical tester outputs, including CSV files, key-value text files, and proprietary formats, into structured and queryable data.
- Design and deploy analytics dashboards for process capability, yield trends, GRR analysis, statistical process control monitoring, and cross-site measurement correlation.
- Implement AI-enabled workflows to support automated GRR validation, build summaries, and specification optimization.
- Establish data governance standards, including role-based access controls, vendor-specific editing permissions, schema versioning, audit logging, and change traceability.
- Partner with metrology engineers and manufacturing partners to gather requirements and translate measurement workflows into scalable system architecture.
- Support site assessments, design meetings, construction reviews, and coordination with design consultants.
- Travel up to 15% as needed.
Qualifications- Bachelor's degree in Computer Science, Data Engineering, Software Engineering, or a related field.
- 5+ years of experience building full-stack web applications using React, TypeScript, and cloud-based backend services.
- 5+ years of experience working with cloud data services such as S3, Lambda, API Gateway, CloudFront, DynamoDB, Athena, or similar tools.
- 5+ years of experience designing data pipelines and data models for manufacturing, quality, IoT, or similar operational systems.
- Strong Python and SQL skills for data processing, transformation, and analysis.
- Experience with Infrastructure as Code tools such as CDK, CloudFormation, or Terraform.
- Strong communication skills and the ability to partner with both software teams and hardware or manufacturing engineering stakeholders.
Preferred Qualifications- Master's degree in Computer Science, Data Engineering, or a related field.
- Experience with statistical process control, GRR methodology, metrology systems, or quality data platforms.
- Experience with manufacturing execution systems, industrial data acquisition systems, or hardware quality workflows.
- Background in optical metrology, display technology, hardware engineering, or manufacturing quality systems.
- Experience with AI/ML agent frameworks or AI-enabled workflow automation.
Top Skills- Cloud data platform development using AWS services, including S3, Lambda, API Gateway, DynamoDB, Athena, and related tools.
- Data pipeline and data model design for manufacturing, quality, metrology, or IoT systems.
- Full-stack application development using React, TypeScript, and cloud-hosted backend services.
Success Measures- Reduction in manual hours required for metrology data analysis.
- Number of programs successfully onboarded to the data platform and analytics dashboards.
- Accuracy, reliability, and scalability of data ingestion, validation, and reporting workflows.
- Successful delivery of secure, maintainable systems that support multiple manufacturing sites and external partners.
Candidate ProfileSuccessful candidates are hands-on full-stack engineers with strong cloud data architecture experience. They are comfortable working across software, data, manufacturing, and quality teams; can independently design scalable systems; and are able to simplify complex measurement workflows through automation, analytics, and AI-enabled tools.
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