Industry 4.0 Engineer

Kaleidoscope Innovation; Lafayette (IN); On-site; USD 80,000 - 120,000; Full time

Job summary

Kaleidoscope Innovation is seeking a full-stack Industry 4.0 contractor in Lafayette, IN. You will help connect manufacturing equipment and transform data into actionable insights while working closely with various teams.

The ideal candidate has 7-20 years of experience in manufacturing data, strong skills in data analysis, and a proven ability to work independently in a contract role. This on-site position offers opportunities to make a significant impact in manufacturing analytics.

Qualifications

• 7-20 years of experience working with manufacturing equipment data.
• Hands-on experience with IIoT sources.
• Proven ability to operate independently in a contract role.

Responsibilities

• Enable and support connections to manufacturing equipment and sensors.
• Structure and prepare machine data for analysis and reporting.
• Develop dashboards and reports for operational insights.
• Lead reviews of data insights with stakeholders.

Skills

Connecting manufacturing equipment data

Data analysis and visualization

Transforming raw data into actionable insights

Collaboration with OT/IT teams

Job description

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.

Location: Lafayette, IN (on-site 5 days a week)

Years of experience required: 7-20 years

Overview

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.

Key Responsibilities

Machine Connectivity & Data Acquisition

• 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.

Data Engineering & Pipeline Development

• 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.

Analytics, Reporting & Insights

• 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.

Operational Integration & Actionability

• 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 (Contract‑Oriented)

• 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.

Required Skills & Experience

• 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.

Preferred / Nice‑to‑Have Experience

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

Kaleidoscope, an Infosys Company, is an equal opportunity employer, and all qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, spouse of protected veteran, or disability.