Forward Deployed Data Engineer

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 Forward Deployed Data Engineer works to understand workflows, data sources, data meaning, and decision needs, then translate those needs into governed Databricks data products, reusable data models, analytics, and AI-enabled solutions. This role reports to a leader in engineering team and works closely with IT, including Data & Analytics, Manufacturing IT/OT, Enterprise Applications, Cybersecurity, and Architecture. The Forward Deployed Data Engineer bridges plant operations, business leadership, and IT to improve enterprise insight while preserving appropriate plant-level flexibility. The role supports manufacturing data strategy by aligning plant data, ETL/ELT[RD1.1][DT1.2], data hierarchy, , metrics, and semantic definitions so plant teams and central leadership can make, faster, trusted data driven decisions. Roles and Responsibilities Understand workflows, constraints, decision points, and data needs embed 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, [... source excerpt omitted ...] yQS, LIMS, CMMS, equipment data, spreadsheets, databases, and other sources at a plant by plant level. Translate ambiguous business and manufacturing problems into practical data requirements, 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. Develop and/or support Databricks-based data products, pipelines, notebooks, dashboards, models, and [... source excerpt omitted ...] 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. Partner with IT architecture, cybersecurity, enterprise applications, integration, infrastructure, and manufacturing IT/OT to meet standards for identity, access, lineage, logging, supportability, resiliency, and responsible AI usage. 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, analyst