Lead Data Architect – Manufacturing Design
Foundation EGI
full-time
Posted on:
Location Type: Remote
Location: Massachusetts • United States
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Job Level
Tech Stack
About the role
- Own the definition and evaluation of output quality, ensuring consistency and accountability across all internal and external datasets.
- Oversee ingestion, cleaning, transformation, and structuring of customer data for AI model training and inference.
- Build scalable processes and frameworks for data labeling, annotation tools, quality checks, and feedback loops.
- Ensure timely, high quality data delivery for internal R&D and customer deployments.
- Own SLAs, accuracy targets, and “definition of quality” for all datasets.
- Partner with Product Managers to shape data-related features, workflows, and tooling (e.g., annotation UI, correction UI, model output review tools).
- Translate customer needs into clear data requirements and repeatable solutions.
- Build and lead a Data Studio team.
- Implement best practices for documentation, quality metrics, repeatable workflows, and compliance.
- Drive continuous improvements in throughput, cost efficiency, and accuracy.
- Work closely with engineering and research teams to define data needs for model training, evaluation, and debugging.
- Collaborate with BD team to scope data requirements for onboarding and implementation.
- Serve as the subject matter expert on data quality, data formats, labeling standards, and customer specific nuances related to manufacturing design.
- Interface with customers to understand their domain, data structures, and quality expectations.
- Guide customers through data preparation, schema definition, and ongoing iteration.
- Own delivery timelines, reporting, and communication for all active data projects.
Requirements
- Domain expertise in manufacturing design or industrial workflows; mechanical engineering background is required.
- Hands-on experience with CAD tools (e.g., SolidWorks, CATIA, Siemens NX, Creo) and familiarity with interpreting complex mechanical models.
- Experience creating or working with technical documentation such as exploded views, work-step sequencing, GD&T drawings, repair manuals, and similar manufacturing/assembly artifacts.
- Ability to work directly with customers and translate domain problems into data requirements.
- Experience leading and growing teams.
- Excellent project management and cross-functional communication skills.
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
data qualitydata ingestiondata cleaningdata transformationdata structuringdata labelingdata annotationdata metricsproject managementmechanical engineering
Soft Skills
leadershipcommunicationcollaborationcustomer engagementproblem-solvingdocumentationcontinuous improvementaccountabilitycross-functional communicationteam building