Industry 4.0 Full Stack Machine Connectivity & Analytics Engineer

Dice is the leading career destination for tech experts at every stage of their careers. Our client, Staffingine LLC, is seeking the following. Apply via Dice today! Role: Industry 4.0 Full Stack Machine Connectivity & Analytics Engineer Expected year of Exp: 7-10 years Location: Lafayette, IN (In plant, No WFH) Role Summary Required Full stack Industry 4.0 contractor 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. \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_ \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_ 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.