Industry 4.0 Engineer

INFOSYS NOVA HOLDINGS LLC•Lafayette, IN

13d•Onsite

About The Position

Seeking a full-stack Industry 4.0 contractor to help accelerate our journey to connect manufacturing equipment, collect and structure machine and process data, and convert that data into actionable, decision-ready insights. This role bridges OT/IT connectivity, data engineering, and manufacturing analytics, partnering closely with manufacturing engineering, operations, controls/IT-OT, and transformation teams. The contractor will focus on rapid enablement, practical solutions, and creating repeatable patterns that scale across assets and facilities.

Requirements

Applicants must be authorized to work for ANY employer in the U.S. We are unable to sponsor or take over sponsorship of an employment Visa at this time.
Hands-on experience connecting or working with manufacturing equipment data, telemetry, or IIoT sources.
Strong ability to transform raw machine/process data into actionable insights, not just dashboards.
Experience with data analysis and visualization tools used in manufacturing or industrial contexts.
Comfort working across OT, IT, engineering, and operations in a plant environment.
Proven ability to operate independently in a contract role with minimal direction.

Nice To Haves

Exposure to reliability, asset performance, predictive maintenance, or process monitoring use cases.
Familiarity with structured deployment playbooks, continuous-improvement cadences, and sustainment models.

Responsibilities

Enable and support connections to manufacturing equipment, sensors, and digital sources in collaboration with controls and IT/OT teams.
Support secure and reliable data collection from machines and systems used in manufacturing operations.
Validate data availability, frequency, signal quality, and basic health of connected assets.
Structure, normalize, and prepare machine and operational data so it is usable for analytics and reporting.
Implement pragmatic data pipelines that support near-real-time and historical analysis (tool-agnostic, fit-for-purpose).
Document data definitions, assumptions, and limitations to enable sustainment and scale.
Develop dashboards, reports, and analytical views that translate raw data into clear operational insights and recommended actions.
Support reporting workflows that may include structured exports (e.g., CSV) and Power BI-style dashboards depending on maturity and use case.
Identify trends, exceptions, thresholds, and opportunities related to safety, quality, throughput, utilization, or reliability.
Support or lead regular reviews of data insights with plant stakeholders to ensure insights turn into actions with owners and follow-up.
Partner with manufacturing engineering, operations, EHS, quality, and IT/OT to ensure analytics align with real shop-floor decisions.
Contribute to development of repeatable deployment patterns and best practices that can be reused across sites.
Deliverables include: Connected asset and data source inventory with signal definitions and data quality notes; Initial analytics package (dashboards and/or reports) tied to specific, agreed-upon operational questions; Documented data pipeline and reporting approach suitable for handoff or replication; Established cadence for insight review and action tracking with plant stakeholders.