Smart Factory Data Engineer
About The Position
The Smart Factory Data Engineer will support Qualitrol’s manufacturing modernization and digital transformation by designing and implementing digital infrastructure that connects production equipment, manufacturing systems, quality systems, and operational processes into a unified industrial data platform. The role bridges factory-floor operations and cloud environments to enable real-time visibility, operational intelligence, and data-driven decision-making. The engineer will establish scalable data acquisition architectures, develop industrial data pipelines, create operational dashboards, and help build a model production cell that demonstrates Industry 4.0 best practices and emerging manufacturing technologies. The work includes integrating on-premises manufacturing systems and edge devices with hybrid cloud architectures using Azure and AWS services. Qualitrol is part of Ralliant Corporation, a public precision-technology company. Qualitrol manufactures monitoring and protection devices for electrical assets and OEM manufacturing companies, including products for partial discharge monitoring and asset protection.
Requirements
- Bachelor’s degree in Computer Science, Data Engineering, Information Systems, Software Engineering, Mathematics, or a related technical field.
- At least 5 years of experience designing and implementing data engineering solutions in manufacturing, Industrial IoT, smart factory, or Industry 4.0 environments.
- Hands-on experience with Azure Data Factory, Databricks, IoT Hub, Synapse/Fabric and AWS IoT Core, Kinesis, Glue, Redshift, S3, or similar technologies.
- Experience integrating factory-floor systems, including PLCs, SCADA systems, machine controllers, sensors, manufacturing databases, and edge platforms.
- Knowledge of industrial communication protocols such as OPC-UA, MQTT, Modbus, Ethernet/IP, or similar technologies.
- Experience building real-time or streaming data architectures and operational dashboards.
- Working knowledge of manufacturing metrics such as OEE, throughput, yield, scrap, downtime, first-pass yield, and cycle time.
Nice To Haves
- Experience supporting Lean Manufacturing, Continuous Improvement, Six Sigma, or Kaizen initiatives is strongly preferred.
Responsibilities
- Design, deploy, and maintain industrial data acquisition solutions connecting production equipment, sensors, PLCs, test systems, MES systems, and quality systems.
- Build and maintain scalable data pipelines to collect, process, transform, and deliver operational manufacturing data.
- Develop real-time and near-real-time data architectures that enable operational visibility and rapid decision-making.
- Design and implement data integration solutions using Industrial IoT platforms and edge-computing technologies.
- Create and maintain operational dashboards covering production performance, quality, throughput, downtime, utilization, and OEE.
- Establish standards and best practices for factory data architecture, governance, connectivity, and scalability.
- Design and implement hybrid cloud architectures using Azure and AWS services while integrating on-premises manufacturing systems and edge devices.
- Lead development of a model production cell demonstrating smart manufacturing, Industry 4.0 best practices, and advanced operational intelligence.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
