Manufacturing Data Engineer - Medical Devices

Description

The company is a diversified manufacturer that helps market-leading brands design, build and deliver new products.

This newly created, full-time role reports to the Senior Manager of Digital Manufacturing.

The role supports a Factory of the Future roadmap across several manufacturing facilities in a regulated medical-device setting.

The engineer builds and maintains the trusted industrial data base that lets factory teams act on what the data shows.

You connect and add context to data from production equipment and manufacturing systems, check automated data for accuracy, and turn operational signals into prioritized, traceable actions for the right teams.

You work with Operations, Manufacturing Engineering, Reliability, Maintenance, Quality and IT/OT, and follow each change from data through decision and action to confirmed business impact.

Responsibilities

• Build and support dependable data pipelines that pull from PLCs, SCADA, historians, MES, CMMS, quality systems and other approved manufacturing sources.
• Define assets, equipment, lines, products, shifts, batches and lots, events, downtime, defects and production states so the data has clear operational meaning.
• Apply industrial information models and suitable ISA-95 concepts, and support scalable event-driven architectures and shared manufacturing data patterns with IT/OT.
• Document source-to-target mappings, calculation logic, lineage, ownership and refresh timing for key manufacturing metrics.
• Check automated data against equipment behavior, production records, operator observations and system-of-record transactions, and trace discrepancies back to their source.
• Build automated checks for completeness, timeliness, duplicates, wrong classifications, sensor faults, missing events and unusual values.
• Work with process owners to set governed definitions and reliable calculations for OEE, availability, performance, quality, scrap, yield, cycle time, downtime and asset performance.
• Triage issues and fix root causes for the data products you own, and provide monitoring, alerts, change control and clear notes on data limitations.
• Turn validated findings into specific action recommendations and task assignments, each with a named owner, priority, supporting evidence, due date and expected operational benefit.
• Tune rules, thresholds, alerts and workflow integrations so exceptions reach the right Operations, Quality, Maintenance, Reliability or Engineering team.
• Define response criteria, escalation paths, closure evidence and feedback loops with process owners, and confirm whether each action fixed the underlying issue.
• Enable Pareto analysis, loss-tree reporting and drill-down work to find repeat causes of scrap, unplanned downtime, lower throughput and quality losses.
• Support predictive and prescriptive use cases such as anomaly detection, predictive maintenance and predictive quality, and make sure results are explainable and validated before anyone uses them on the floor.
• Build reusable, maintainable data models, SQL and Python transformations, APIs and analytics-ready datasets for dashboards and future AI applications.
• Work with Digital Manufacturing leaders on use-case priorities, requirements, technical feasibility, rollout and adoption across factories.
• Work with IT and OT cybersecurity teams to meet architecture, access, network segmentation, security, backup and support requirements, without bypassing established controls.
• Support regulated manufacturing requirements through documented testing, change management, traceability and the quality-system procedures that apply.
• Measure value through better data trust, less manual reconciliation, completed actions, and verified gains in scrap, OEE, yield, downtime and operating performance.

Requirements

• Bachelor's degree in Engineering, Computer Science, Data Engineering, Information Systems or a closely related technical field, or equivalent relevant experience.
• 6+ years of relevant experience in manufacturing data engineering, industrial systems integration, manufacturing analytics or industrial automation.
• Hands-on skill in SQL and Python for transforming, analyzing, validating and integrating data.
• Working knowledge of industrial equipment data and at least some of PLCs, SCADA, historians, MES, CMMS or manufacturing quality systems.
• Experience building and troubleshooting data pipelines, data models, APIs or event-based integrations.
• Ability to investigate discrepancies directly with manufacturing teams and turn complex data into practical, measurable shop-floor actions.
• Strong analytical problem-solving, documentation, communication and cross-functional collaboration skills.
• Preferred: experience in medical-device or other regulated manufacturing, and familiarity with ISO 13485 and FDA quality-system expectations.
• Preferred: familiarity with MQTT, unified namespace patterns, OPC UA, ISA-95, time-series data and industrial data historians.
• Preferred: experience with Power BI, semantic models, cloud or hybrid data platforms, streaming tools and CI/CD or automated testing.
• Preferred: exposure to OEE, scrap and yield analytics, maintenance reliability, statistical process control, machine learning or predictive quality.
• Preferred: experience connecting analytics outputs to CMMS, MES, ticketing or workflow systems to create and track corrective actions.

Conditions

Full-time position based at the company's 24x7 manufacturing site in Buffalo Grove, IL, with occasional work at the new Libertyville, IL site.

No travel is required.

Base pay ranges from $99,900.00 to $137,400.00 USD per year; the final rate depends on job-related, non-discriminatory factors such as experience, qualifications, location, education, external market data and internal equity.

No visa sponsorship is available for this role.

Applications are accepted for at least five days after the posting start date of 10-15-2026, through the end date of 12-20-2026 or until the role is filled, and may close earlier due to volume.

The company is an equal opportunity employer that makes decisions on merit, qualifications and abilities without regard to protected status, and it provides reasonable accommodations on request.

Benefits

• Medical, dental and vision plan options.
• Life insurance.
• Short-term and long-term disability coverage.
• Matching 401(k) contributions.
• Vacation and paid sick time.
• Tuition reimbursement.