Data Infrastructure Engineer

Overview

We’re seeking a Data Infrastructure Engineer who’s ready to put your skills to work on projects that matter — and build a career with a company that’s building North America.

Job Title: Data Infrastructure Engineer | Req : 15562 |
HR Contact: |

Location:

Dundee Office MI, Alpena Cement Plant MI, Chicago Office IL, Ste. Genevieve Cement MO

The Data Infrastructure Engineer participates in maintenance and development of IoT related software tools. This role is responsible for ensuring the integrity, reliability, and ongoing optimization of data transfer processes and data-related operational technology (OT) infrastructure. This role oversees the systems and pipelines that move plant and equipment data into enterprise platforms, ensuring high availability, strong data quality, and secure communication.

• Maintain and enhance OT Data Infrastructure by overseeing, maintaining, and optimizing the systems that collect, process, and transfer operational data from plant equipment to enterprise platforms.
• Develop and Maintain IoT Software Tools by designing, building, and updating software tools, scripts, and utilities that support IoT device management, data extraction, health monitoring, and automated workflows in the OT environment.
• Ensure Data Integrity and Quality by implementing validation routines, monitoring dashboards, and automated checks to guarantee accurate, complete, and reliable data across all sources.
• Monitor and Manage Data Transfer Pipelines by continuously tracking the performance of data flows, identifying failures or slowdowns, and ensuring timely, high-availability data delivery.
• Collaborate Across Technical Teams and work closely with IT, automation, engineering, cybersecurity, and analytics teams to support new integrations, platform improvements, and organizational data initiatives.
• Implement Infrastructure Improvements and Upgrades by identifying opportunities to enhance data architecture, streamlining pipelines, and modernizing OT data systems and IoT ecosystems.
• Document Systems, Tools, and Procedures by maintaining detailed documentation of data flows, IoT software tools, configurations, incident resolutions, and infrastructure changes.
• Support the Deployment of New Technologies by participating in the rollout of new sensors, IoT platforms, connectivity solutions, or data tools, ensuring seamless integration with existing systems.
• Demonstrate a commitment to communicating, improving and adhering to health, safety and environmental policies in all work environments and areas. Promote a culture of safety and exhibit these behaviors.

Education: Bachelor's degree or years of equivalent experience

Additional Education Preferred: Master's degree

Field of Study Preferred: Software development or Computer Science / BSc

Required

Work Experience:

5 years industrial manufacturing

Required Technical

Skills:

Python programming, Node.js or JavaScript/Type Script, SQL, OPC/Industrial Protocol Libraries, Containerization (Docker), SAP a plus.

Travel Requirements: 20%

• Skills in Cloud or Edge Platform SDKs, Data Pipeline Tools / Framework, Basic Front-End Skills
• Affinity to digital and technology development and implementation to deliver improved operational efficiencies
• Strong communication, coordination skills & ability to energize stakeholders
• Understanding of industrial control systems (PLC) and information technology networks (e.g. TIS – technical information system), data acquisition and historian systems
• Understand process and equipment monitoring, sensors, networks and digital
• Agile learning approach
• Innovative mind set and track record
• Artificial intelligence and machine learning desired
• Successful candidates must adhere to all safety protocols and proper use of Amrize approved PPE
• Personal Protection Equipment ("PPE"), including but not limited to respirators. Subject to applicable law, employees that are required to wear respirators must be clean shaven where the respirator seal meets the face in order to pass the qualitative and quantitative fit tests.