Forward Deployed Data Engineer

Job summary

It's exciting to work for a company that makes the world measurably better. We're committed to bringing safety, quality, and customer focus to the business of advanced ceramics manufacturing. Job Title Forward Deployed Data Engineer Must be a U.

Qualifications

• data products, analytics, applications, and implementation plans.
• Define mappings, data definitions, transformation rules, business logic, data quality rules, and metric calculations for trusted manufacturing insights.
• Help establish an aligned manufacturing data hierarchy across sites, equipment, work centers, operations, products, materials, orders, quality events, and maintenance events.
• Partner with IT Data & Analytics on ETL/ELT patterns using Databricks, Delta Lake, Unity Catalog, workflows, governed tables, semantic definitions, and reusable data assets.
• Support project-based data collection, cleaning, and integration efforts at the plant level to enable broader digitalization initiatives.
• Improve data capture, completeness, quality, and ownership where source data is inconsistent, manual, incomplete, or not decision-ready.
• Create minimum viable data products with real users, then mature successful solutions into governed, supportable production patterns, including Databricks-hosted applications.
• Document lineage, transformation logic, business definitions, solution designs, runbooks, ownership models, and reusable patterns that can scale across plants and business units.
• Coach plant engineers, analysts, and business users on data definitions, data quality, workflows, analytics adoption, and responsible AI-enabled capabilities.
• Serve as a point of contact for feedback loop between the business and IT by identifying recurring plant needs, architecture gaps, and reusable platform improvements.
• Education
• Bachelor’s degree in Engineering, Industrial Engineering, Manufacturing Systems, Data Analytics, Computer Science, Information Technology, or a related field required.

Responsibilities

• Understand workflows, constraints, decision points, and data needs embedded with manufacturing sites, business units, and functional teams.
• Identify high-value opportunities for data, analytics, AI, or workflow enablement by partnering with plant leaders, engineers, quality, supply chain, maintenance, finance, and business leaders.
• Executes hands-on, plant-level initiatives focused on improving efficiency, reducing manual work, and enabling AI and automation use cases.
• Focus on digitalization of shop-floor processes, including elimination of paper-based workflows and improving data capture completeness.
• Assess manufacturing data alignment across SAP, QAD, Apriso, Ignition, InfinityQS, LIMS, CMMS, equipment data, spreadsheets, databases, and other sources at a plant by plant level.
• Translate ambiguous business and manufacturing problems into practical data

Skills

Degrees

Travel

Industry

Company size