Hermeus - Enterprise Data Architect
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Requirements
• Bachelors degree in Computer Science, Information Systems, Software engineering, or similar • 6+ years building and scaling enterprise data platforms • Deep SQL expertise (query optimization, indexing, execution plans, modeling discipline) • Experience designing ODS-style integration layers and dimensional warehouse architectures • Experience integrating multiple enterprise systems (ERP, HRIS, manufacturing, Engineering systems, SaaS platforms) • Strong understanding of canonical modeling and fact/dimension design • Experience implementing incremental load and change-detection strategies • Experience supporting enterprise BI platforms (Power BI or equivalent) • Ability to translate business complexity into scalable data structures • Experience in manufacturing, aerospace, or hardware-driven environments • Experience scaling data platforms in mid-stage growth companies • Exposure to data governance frameworks and metadata management • Experience evaluating cloud data platform evolution strategies • $142,500 - $235,750 a year
Responsibilities
• Enterprise Data Architecture & Modeling • Define and evolve the enterprise data architecture across PLM,ERP, MES, HR, IT • Establish dimensional modeling standards (fact/dimension conventions) and canonical entity definitions • Design scalable integration patterns that support onboarding new systems without structural rework • Align operational and analytical models • Cross-System Canonical Data & Integration Governance • Define and maintain canonical enterprise entities • Establish enterprise-wide naming conventions, data ownership standards, data definitions across systems and modeling governance • Partner with application owners to align upstream system design with downstream analytics needs • Ingestion, Reliability & Platform Performance • Strengthen ingestion reliability, monitoring, and change-detection patterns • Improve performance through indexing, partitioning, and workload optimization • Implement scalable incremental load strategies and reconciliation processes • Ensure platform stability as data volume and system count increase • Analytics & Semantic Layer Governance • Centralize business logic currently dispersed across BI models • Establish reusable semantic patterns that simplify reporting and metric consistency • Improve Power BI performance and model clarity • Data Quality & Traceability • Implement pragmatic governance standards (lineage, ownership, quality checks) • Define history and audit strategies where required (financial traceability, manufacturing effectivity, people/device lifecycle changes) • Identify systemic data quality trends and drive structural improvements • Long-Term Data Strategy & Platform Evolution • Define and own the enterprise data architecture roadmap • Evaluate platform and tooling evolution decisions based on measurable business impact • Influence cross-functional enterprise technology decisions related to data integration and analytics infrastructure • Enable advanced analytics, forecasting, optimization, and AI-driven capabilities • Lay the foundation for a future enterprise data function • 100% employer-paid health care • 401k & retirement plans • Unlimited PTO • Weekly paid office lunches • Fully stocked breakrooms • Stock options • Paid Parental Leave • U.S. EXPORT CONTROL COMPLIANCE STATUS • The person hired will have access to information and items subject to U.S. export controls, and therefore, must either be a “U.S. person” as defined by 22 C.F.R. § 120.62 or otherwise eligible for deemed export licensing. US persons include U.S. citizens, U.S. nationals, lawful permanent residents (green card holders), and asylees and refugees with such status granted, not pending. • EQUAL OPPORTUNITY
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