Data Engineer IoT PLC Machinery Industrial Data pushes and pulls, new

Job Description

Job Description

We are seeking a Senior Metrology Data Engineer to lead the data access and analysis of the metrics surrounding raw vs. end materials after tooling. In this role, you will bridge the gap between high-precision dimensional inspection hardware (CMMs, 3D laser scanners) and data.

You will not just extract dimensional data—you will design, build, and optimize automated ETL pipelines to ingest, clean, and model spatial and geometric datasets. By combining GD&T (Geometric Dimensioning and Tolerancing) data by using Python or other modern data tools, you will transform raw coordinate datasets into real-time, factory-wide Statistical Process Control (SPC) insights and predictive quality analytics.

Core Duties & Responsibilities

• Build & Maintain Metrology ETL Pipelines: Design and deploy automated data extraction, transformation, and loading (ETL) pipelines to ingest raw, unstructured, and semi-structured outputs (DMO, CSV, XML, JSON) from CMMs and 3D scanners into centralized databases or data lakes.
• Python-Driven Data Analytics: Leverage Python data libraries (pandas, NumPy, SciPy) to clean raw spatial coordinates, parse geometric output files, handle missing/anomalous measurements, and compute complex custom statistical metrics.
• Automate Statistical Process Control (SPC): Develop scripts to automatically monitor tolling wear and geometric drift by continuously calculating and updating process capability metrics ($C_p$ and $C_{pk}$) across high-volume production lines.
• CMM/Scanner Data Integration: Partner with Machine R&D Engineering to standardize output schemas and implement Model-Based Definition (MBD) protocols, ensuring physical measurements perfectly align with digital 3D CAD dimensions via automated workflows.
• Database Management & Data Modeling: Schema design and management of SQL/NoSQL databases dedicated to quality metrics. Optimize queries to handle high-frequency time-series measurement data coming from multiple production lines.
• Data Integrity & MSA Automation: Program automated scripts to process Gauge R&R data and generate automated Measurement System Analysis (MSA) reports, ensuring the validity and repeatability of factory sensor data.

Desired Skills/Experience:

• Education: Bachelor’s degree in Data Engineering, Computer Science, Mechanical/Manufacturing Engineering with a strong programming focus, or equivalent technical experience.
• Experience: 5+ years of experience in data engineering or quality analytics, with a distinct focus on processing industrial, manufacturing, or spatial/dimensional data.
• The Python Data Stack: Expert proficiency in Python, specifically for data manipulation and analysis (pandas, NumPy) and data engineering/ETL workflows. Experience with workflow orchestration tools (e.g., Airflow, Prefect) is a major plus.
• SQL & Database Expertise: Strong proficiency in writing advanced SQL queries, designing database schemas, and managing relational databases (PostgreSQL, MS SQL Server) or time-series databases.
• CI/CD & Version Control: Experience using Git and version control best practices to maintain quality-data infrastructure and script deployments.

Pluses: (nice to have/should be willing to learn):  Metrology & GD&T Literacy/fundamental understanding of Geometric Dimensioning and Tolerancing (GD&T) principles (ASME Y14.5) and familiarity with metrology software file architectures (e.g., PC-DMIS, Zeiss Calypso, PolyWorks).

Very Competitive Compensation and Benefits (Relocation Assistance is offered), Call or Apply Today!

Very Stable, U.S. based manufacturing company with customers in various industries.

Company Description

Very Stable, U.S. based manufacturing company with customers in various industries.