IT/OT Data Engineer

Merz•Racine, WI

50d

About The Position

As the organization's initial data engineering hire, this position will develop and support reliable OT to MES/UNS pipelines, integrate enterprise applications (ERP, QMS, complaints) through REST/SOAP APIs, and help establish repeatable integration practices for the data platform. Furthermore, they will collaborate with the first data scientist to build and maintain the organization's digital backbone.

Requirements

Bachelor's Degree Data Engineering or Computer Science
3-5 years of data engineering and/or systems integration, with strong exposure to industrial/OT data or high-throughput production systems
3-5 years of hands-on experience with OPC UA, AMQP and SCADA gateways.
3-5 years working with REST/SOAP APIs, schema evolution, and CDC patterns.
2+ years working in GxP environments with awareness of CSV expectations.

Nice To Haves

Experience integrating MES, ERP, QMS, lab equipment and SCADA.
Experience working with Ignition, Litmus, and Fuuz.
Experience working with prompt engineering large language models.

Responsibilities

Pipeline Engineering (Batch & Streaming) Design, implement, and operate reliable batch and streaming pipelines from OT and enterprise systems to the UNS and analytics platforms, implement event/streaming ingestion (e.g., MQTT, Kafka/Azure Event Hubs) and high-throughput batch workflows, and ensuring performance, scalability, and maintainability.
Systems Integration Connect laboratory and shop-floor equipment to MES, ELN, LIMS and/or the UNS (e.g., OPC UA servers, Kepware, Ignition, industrial gateways), and integrate enterprise applications via REST/SOAP APIs, file drops/EDI, and CDC/connectors (e.g., ERP, QMS, CRM, complaints), with appropriate data contracts and versioning.
Platform, CI/CD, and Reliability Build Infrastructure-as-Code (IaC) environments and implement CI/CD for data pipelines, including automated unit, integration, and data quality testing, and establish observability (logging, metrics, tracing), define SLAs/SLOs/SLIs, and author runbooks to support on-call operations and continuous improvement.
Security, Compliance, and Validation Enforce least-privilege access, OT/IT network segmentation (including DMZ patterns), and secure secrets management and collaborate on CSV/GAMP 5 deliverables and ensure audit trails and change controls aligned to 21 CFR Part 11.
Collaboration and Standards Partner with data science and cross-functional stakeholders to define and maintain data contracts, schemas, and naming conventions and develop reusable connectors, templates, and documentation to accelerate future integrations and promote consistency.