Job description

Role: Smart Factory Data Engineer Location: Fairport, NY This is an outstanding place to work! It all starts with the people. You will love working with colleagues who have a genuine desire to innovate and solve complex problems. We come to work every day striving to make the organization better than it was the day before—asking tough questions, pushing boundaries, and supporting each other in an environment that values authenticity, clarity, inclusion, and diversity. Qualitrol associates enjoy the autonomy, breadth of responsibility, and creativity typical of a medium-sized company, while benefiting from the resources, standard methodologies, and career opportunities of a Fortune 500 organization like Ralliant. Your Impact As a Smart Factory Data Engineer, you will play a pivotal role in Qualitrol's manufacturing modernization and digital transformation journey. You will be responsible for designing and implementing the digital infrastructure that connects production equipment, manufacturing systems, quality systems, and operational processes into a unified industrial data platform. This role bridges the factory floor and the cloud, enabling real-time visibility, operational intelligence, and data-driven decision making across manufacturing operations. You will establish scalable data acquisition architectures, develop industrial data pipelines, create operational dashboards, and help build a model production cell that showcases Industry 4.0 best practices and emerging manufacturing technologies. Here’s Where You’ll Demonstrate Your Proficiency • Design, deploy, and maintain industrial data acquisition solutions that connect production equipment, sensors, PLCs, test systems, MES systems, and quality systems. • Build and maintain scalable data pipelines that 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 utilizing Industrial IoT platforms, and edge computing technologies. • Create and maintain operational dashboards that provide insight into 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 leveraging 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. The Successful Candidate Will Demonstrate the Following Skills and Experience • Bachelor's degree in Computer Science, Data Engineering, Information Systems, Software Engineering, Mathematics, or a related technical field. • 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 including 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 including OEE, throughput, yield, scrap, downtime, first-pass yield, and cycle time. • Experience supporting Lean Manufacturing, Continuous Improvement, Six Sigma, or Kaizen initiatives is strongly preferred. #LW-PW1

Requirements

Must-haves

Role: Smart Factory Data Engineer
Location: Fairport, NY
This is an outstanding place to work!
Here’s Where You’ll Demonstrate Your Proficiency
Design, deploy, and maintain industrial data acquisition solutions that connect production equipment, sensors, PLCs, test systems, MES systems, and quality systems.
Build and maintain scalable data pipelines that 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 utilizing Industrial IoT platforms, and edge computing technologies.
Create and maintain operational dashboards that provide insight into 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 leveraging 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.
The Successful Candidate Will Demonstrate the Following Skills and Experience
Bachelor's degree in Computer Science, Data Engineering, Information Systems, Software Engineering, Mathematics, or a related technical field.
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 including 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 including 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.

Application prep

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Keywords to mirror

azureaws

Platform: oracle-cloud
Effort: medium