Smart Factory Data & Digital Twin Engineer

Precision Castparts Corp. (PCC)

Langhorne (Bucks County)

On-site

USD 120,000 - 180,000

Full time

2 days ago

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Job summary

Precision Castparts Corp. is building a smart aerospace manufacturing facility and seeks an experienced Manufacturing Systems & Digital Integration Engineer to design and enable the facility's digital backbone.

You will define how digital models, data architecture, and connected systems simulate, predict, and optimize operations. You will collaborate with Automation & Controls engineers and site leadership to implement the infrastructure for real-time visibility, enhanced control, and

Qualifications

7-10+ years of experience in Computer Science, Mechatronics, Industrial automation and controls.
Strong experience with data-driven improvement initiatives or digital manufacturing tools.
Development of data collection and system integration for a manufacturing facility.
Experience with integrating PLC programming (Allen-Bradley, Siemens, or similar).

Responsibilities

Design data pipelines connecting PLCs, SCADA, MES, ERP, and IIoT systems.
Define data structures, tagging strategies, and governance standards.
Define how machine data translates into operational metrics (OEE, downtime, yield).
Ensure scalable and reliable data flow across systems.
Collaboration and discovery of existing data platforms and coordination for enterprise-wide interoperability.
Apply statistical and machine learning techniques to improve system performance and predictive capabilities.
Develop models for predictive maintenance, throughput optimization, and anomaly detection.
Combine physics-based simulation with data-driven methods to improve digital twin accuracy.
Enable decision-making through dashboards, visualization tools, and simulation outputs.
Perform scenario analysis, capacity modeling, and system optimization.
Collaborate with teams to optimize manufacturing production and future automation.
Analyze workflows, material flow, and system constraints.
Identify bottlenecks and improvement opportunities using data and on-the-floor observations.
Support layout design, capacity planning, and process optimization.
Validate model accuracy and system performance against real-world operations.