Manufacturing Data Product Analyst

Deep Digital Solutions Group

$80K — $110K *
Manufacturing & Automotive
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 5-7 years of experience in manufacturing systems or industrial automation
  • Proficiency in data architectures and integration principles
  • Familiarity with Unified Namespace (UNS) and Industrial DataOps
  • Experience in developing data pipelines and integration solutions
  • Knowledge of platforms like HighByte Intelligence Hub or HiveMQ
  • Degree in Engineering, Computer Science, or related field required

Responsibilities

  • Design and deploy Unified Namespace (UNS) and industrial data solutions
  • Translate manufacturing requirements into scalable data models
  • Develop and maintain industrial data products for various initiatives
  • Support data pipelines connecting plant-floor systems to applications
  • Implement data transformation and governance processes
  • Configure and maintain industrial data brokers and historians
  • Collaborate with multiple teams for project delivery

Benefits

  • Access to cutting-edge technologies in industrial data management
  • Opportunity to work on transformative data solutions
  • Professional growth in modern industrial data architectures
  • Collaboration with diverse teams across operations and IT
  • Engagement with industry best practices and emerging technologies
Full Job Description
This role will focus on the design, configuration, and implementation of industrial data products, data pipelines, and integration solutions. Working closely with Data Enablement Leads, OT engineers, IT teams, and manufacturing stakeholders, you will help transform operational requirements into scalable data solutions that improve visibility, decision-making, and enterprise connectivity.

This is an excellent opportunity for someone with a strong technical foundation in manufacturing systems, industrial data platforms, and system integration who is looking to further develop their expertise in modern industrial data architectures, including Unified Namespace (UNS), DataOps, MQTT, and enterprise data platforms.

Requirements
  • Support the design, development, and deployment of Unified Namespace (UNS), Industrial DataOps, and industrial data solutions.
  • Assist in translating manufacturing and business requirements into scalable data models and integration architectures.
  • Develop, configure, and maintain industrial data products that support manufacturing, quality, maintenance, and business intelligence initiatives.
  • Design and support data pipelines that connect plant-floor systems with enterprise applications and analytics platforms.
  • Implement data transformation, contextualization, validation, and governance processes.
  • Configure and support industrial data brokers, messaging infrastructure, historians, and integration platforms.
  • Collaborate with Data Enablement Leads, manufacturing teams, OT engineers, IT personnel, and implementation partners on project delivery.
  • Contribute to the development and adoption of technical standards, best practices, and data governance frameworks.
  • Support testing, deployment, troubleshooting, and continuous improvement activities across Data Enablement initiatives.
  • Stay informed on emerging technologies and industry best practices within industrial data management and smart manufacturing.


  • Experience working with manufacturing systems, industrial automation, or industrial data solutions.
  • Knowledge of industrial data architectures, data modelling, and system integration principles.
  • Familiarity with Unified Namespace (UNS), Industrial DataOps, MQTT, or similar industrial data frameworks.
  • Experience developing or supporting data pipelines, data integration, or industrial software solutions.
  • Exposure to platforms such as HighByte Intelligence Hub, HiveMQ, AVEVA PI System (OSIsoft PI), or comparable technologies.
  • Understanding of manufacturing operations and OT/IT environments.
  • Familiarity with industrial middleware, historians, and enterprise integration platforms.
  • Strong analytical and problem-solving skills with the ability to work through technical challenges independently and as part of a team.
  • Excellent communication and collaboration skills.
  • Degree in Engineering, Computer Science, Information Technology, Data Engineering, or a related discipline, or equivalent practical experience.

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