Our client is seeking a highly technical Senior Data Engineer to join their Data Intelligence & Systems Architecture (DISA) team. This engineer will play a foundational role in shaping the enterprise data platform, owning ingestion, modeling, and activation of data that powers reporting, decision-making, and automation across the organization.
This role partners directly with teams across Supply Chain & Manufacturing, Finance & Accounting, HR, Software, Field Operations, and R&D. The ideal candidate combines strong data engineering expertise with business curiosity, high ownership, and a bias toward action.
Ranked Must-Haves
- Highly technical data engineering skillset
- End-to-end ownership of data infrastructures or projects with measurable business impact
- Personable, collaborative, action-oriented, and comfortable working fully on-site
Role Focus Areas : Material Operations
Data pipelines supporting concrete production workflowsSupply chain analyticsCost tracking, forecasting, inventory managementHardware Reliability
Machine and equipment performance monitoringPredictive maintenance analyticsField service ticket analysisTechnical Requirements
Strong Python scripting (required)SQL proficiency (preferred)Palantir Foundry experience (highly valued but not required)Alternative experience : AWS, Snowflake, Power BIProven end-to-end data infrastructure ownershipExperience with IoT / hardware analytics (plus)Experience integrating data from APIs, machine data sources, ERP systems, SaaS tools, and cloud storage platformsCore Responsibilities
Lead ingestion and transformation pipelines across internal tools, SaaS systems, and industrial data sourcesModel and maintain governed, high-quality data assets for reporting, diagnostics, forecasting, and automationBuild analytics frameworks and operational dashboards with real-time visibility into cost, progress, equipment status, and material flowPartner with business and technical stakeholders to translate pain points into scalable data solutionsDevelop advanced analytics capabilities including predictive maintenance and proactive purchasing workflowsImplement best practices in reliability, versioning, documentation, and testingMentor team members and support a culture of excellence in data engineeringMinimum Qualifications
8+ years in data engineering, analytics engineering, or backend software developmentBachelor's degree in Computer Science, Data Engineering, Software Engineering, or related fieldHands-on expertise with Python and SQLExperience delivering scalable data products in fast-paced environmentsStrong understanding of data modeling, business logic abstraction, and stakeholder engagementPreferred Experience
Supporting Manufacturing, Field Operations, or Supply Chain teams with near real-time analyticsFamiliarity with platforms such as Procore, Coupa, or NetSuiteBuilding predictive models or workflow automationBackground in data governance, observability, or maintaining production-grade pipelines