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Industrial Data Engineer Jobs (NOW HIRING)

GEA Group

$91K - $109K/yr

Responsibilities / Tasks The Industrial Data Engineer is responsible for designing, developing, and maintaining scalable data pipelines, databases, and analytics platforms that support cloud-based ...

IP Corporation

Sr. Data Engineer

Saint Paul, MN · On-site

$115K - $145K/yr

Sr. Data Engineer, Microsoft Fabric & Power BI Location: Vadnais Heights, MN (Hybrid) What is IP ... The ideal candidate is passionate about modern data platforms, industrial data integration, and ...

IP Corporation

Sr. Data Engineer

North Saint Paul, MN · On-site

$115K - $145K/yr

The Sr. Data Engineer, Microsoft Fabric & Power BI is responsible for designing, building, and ... The ideal candidate is passionate about modern data platforms, industrial data integration, and ...

MPW

Industrial Data Systems Engineer

Hebron, OH

... Engineering, vendors, and other stakeholders, including sound judgment on when to escalate issues. What You'll Do * Own and support the industrial data historian platform and the systems that collect ...

Shaw Industries Group, Inc.

$61K - $79K/yr

Industrial Data & Controls EngineerPosition Overview Join a Team Where Innovation Meets Real-World Impact We're looking for a Controls & Automation Engineer to join our Divisional Engineering team ...

Truck-Lite

Industrial Data Analytics Engineer

Mcelhattan, PA · On-site

$64K - $86K/yr

... Industrial or Manufacturing Engineering degree with Data Analytics specialization preferred • Specific Skills and/or Experience with Software, Equipment, etc.: • Databases and Platforms: Db2 SQL ...

CoorsTek, Inc.

Forward Deployed Data Engineer

Golden, CO · On-site

$118K - $142K/yr

Bachelor's degree in Engineering, Industrial Engineering, Manufacturing Systems, Data Analytics, Computer Science, Information Technology, or a related field required. * Master's degree preferred.

FastTek

Data Engineer

Dearborn, MI

$105K - $126K/yr

As a Data Engineer on the Wrangling and Visualization Migration Team, you will communicate and ... Experience with any of the ETL, data integration products or any industrial data service.

CoorsTek

Forward Deployed Data Engineer

Golden, CO · On-site

$118K - $142K/yr

Bachelor's degree in Engineering, Industrial Engineering, Manufacturing Systems, Data Analytics, Computer Science, Information Technology, or a related field required. * Master's degree preferred.

Ascentt

Data Engineer

Plano, TX · On-site

$109K - $131K/yr

We partner with global manufacturing enterprises to convert complex industrial data into actionable, real-time business insights. Our teams work on scalable, high-impact engineering challenges across ...

CoorsTek

Forward Deployed Data Engineer

Potsdam, NY · On-site

$124K - $149K/yr

Education Bachelor's degree in Engineering, Industrial Engineering, Manufacturing Systems, Data Analytics, Computer Science, Information Technology, or a related field required. Master's degree ...

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Industrial Data Engineer information

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How much do industrial data engineer jobs pay per year?

As of Sep 14, 2026, the average yearly pay for industrial data engineer in the United States is $83,498.00, according to ZipRecruiter salary data. Most workers in this role earn between $70,000.00 and $94,500.00 per year, depending on experience, location, and employer.

What is an industrial data engineer?

An Industrial Data Engineer is a professional who designs, develops, and maintains data systems specifically for industrial environments such as manufacturing plants, utilities, or supply chains. They focus on collecting, processing, and analyzing data from industrial equipment and processes to optimize performance, improve efficiency, and support decision-making. Their work often involves integrating data from sensors, control systems, and enterprise platforms, ensuring data quality, and enabling advanced analytics such as predictive maintenance and process optimization.

How does an industrial data engineer typically collaborate with operations and maintenance teams on data-driven projects?

Industrial Data Engineers frequently work closely with operations and maintenance teams to understand equipment performance, process flows, and areas for efficiency improvement. They gather requirements from these teams, design data collection systems, and translate operational challenges into actionable data solutions. Regular communication ensures that the data pipelines and analytics they develop are practical and directly support production goals. This collaboration not only improves asset reliability and process optimization but also helps data engineers gain valuable domain knowledge to drive impactful insights.

What are the key skills and qualifications needed to thrive as an industrial data engineer, and why are they important?

To thrive as an Industrial Data Engineer, you need strong expertise in data engineering, industrial automation, and programming languages such as Python or SQL, usually supported by a degree in engineering, computer science, or a related field. Familiarity with industrial IoT systems, SCADA, cloud platforms, and certifications like AWS Certified Data Analytics or Microsoft Azure Data Engineer are typically required. Excellent problem-solving, communication, and teamwork skills help you work effectively with multidisciplinary teams and stakeholders. These skills are essential for designing robust data pipelines and analytics solutions that optimize manufacturing processes and drive operational efficiency.

What is the difference between Industrial Data Engineer vs Data Analyst?

AspectIndustrial Data EngineerData Analyst
CredentialsBachelor's in Engineering, Computer Science, or related field; certifications in data engineering or cloud platformsBachelor's in Statistics, Mathematics, or related field; certifications in data analysis tools
Work EnvironmentIndustrial settings, manufacturing plants, or data centersOffice environments, corporate or business settings
Industry UsageManufacturing, energy, logistics, and industrial sectors

Industrial Data Engineers focus on designing and maintaining data infrastructure for industrial processes, integrating sensor data, and optimizing manufacturing operations. Data Analysts interpret data to generate reports and insights for business decisions. While both roles handle data, Industrial Data Engineers build the systems that Data Analysts use to analyze industrial data effectively.

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Cities with the most Industrial Data Engineer job openings:

What states have the most Industrial Data Engineer jobs?

States with the most job openings for Industrial Data Engineer jobs include:

What are popular job titles related to Industrial Data Engineer jobs?

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Industrial Data Engineer jobs near you
Infographic showing various Industrial Data Engineer job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 84% Full Time, 12% Part Time, and 2% Contract. Highlights an 85% Physical, 3% Hybrid, and 12% Remote job distribution, with an average salary of $83,498 per year, or $40.1 per hour.

Industrial Data Engineer

On-site, Remote

GEA Group
See more jobs at GEA Groupexternal

$91K - $109K/yr

Full-time

Posted 12 days ago

Job description

Responsibilities / Tasks

The Industrial Data Engineer is responsible for designing, developing, and maintaining scalable data pipelines, databases, and analytics platforms that support cloud-based digital applications for food and beverage processing plants. Working closely with Product Owners, Software Developers, Automation Engineers, and Process Experts, this role enables advanced analytics, AI solutions, predictive maintenance, asset performance monitoring, and operational reporting.

This position can be based in Alcobendas (Spain), Naas (Ireland) or Bogota (Colombia), depending on the selected candidate.

  • Design, develop, and maintain data solutions leveraging Microsoft Azure, Databricks, InfluxDB, Industrial IoT data sources, and modern data engineering practices.
  • Design, develop, and maintain ETL/ELT pipelines to support data integration and analytics.
  • Design data models, relationships, and schemas that support analytics, reporting, machine learning, and digital products.
  • Develop API-based integrations using REST services and JSON.
  • Establish standards for data quality, governance, security, and lifecycle management.
  • Ensure data architectures are scalable, reliable, and aligned with enterprise standards.
  • Support the integration of operational and equipment data from industrial systems into enterprise and cloud platforms.
  • Collaborate with cross-functional teams to deliver data-driven solutions and enable business value through analytics and AI.

Your Profile / Qualifications

Educational Background
  • Bachelor's orMaster's Degree in Computer Science, Data Science, Engineering, or a related field.
  • Microsoft Azure or Databricks Certifications.
Professional Knowledge & Experience
  • 3-7 years of experience in Data Engineering, Cloud Data Platforms, or Analytics Solutions.
  • Experience developing Azure cloud-based data solutions.
  • Experience working with large volumes of time-series and industrial data.
  • Strong knowledge of:
    • Data Modelling
    • Data Governance
    • Metadata Management
    • Time-Series Database Design
    • Query Optimization
    • Workflow Orchestration
    • REST APIs
  • Proven experience working in Agile/Scrum environments.
  • Awareness of IEC 62443 standards.
  • Desirable knowledge of Machine Learning, AI, and Data Science concepts, with experience supporting AI-driven analytics solutions.
  • Fluent English (B2/C1) required.
  • Spanish or German would be considered a strong advantage.
Skills & Competencies
  • Strong ethics, compliance, and professionalism
  • Commitment and alignment with business strategies and policies
  • Customer-focused and sustainability-oriented mindset
  • Cross-functional and multidisciplinary collaboration
  • Excellent communication and networking skills
  • Strong listening skills and cultural awareness
  • Strong analytical, problem-solving, and decision-making skills
  • Continuous improvement mindset and commitment to innovation
  • Adaptability and willingness to learn new tools, technologies, and methodologies

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