Enterprise Data Architect

Hermeus•Atlanta, GA

About The Position

Hermeus is a high-speed aircraft manufacturer focused on the rapid design, build, and test of high-Mach and hypersonic aircraft for the national interest. Working directly with the Department of Defense, Hermeus delivers capabilities that will ensure that our nation, and our allies, maintain an asymmetric advantage over any and all potential adversaries. Hermeus is building a unified enterprise data platform as a core pillar of its digital transformation. This platform integrates ERP, Manufacturing, Engineering, HR, IT, and operational systems into a scalable foundation that supports decision-making, analytics, and long-term digital thread continuity. To ensure our data architecture scales with the complexity of our business, we are creating the foundational role of Enterprise Data Architect. This individual will establish and evolve the architectural foundation that ensures enterprise data is accurate, structured, governed, and ready for analytics and operational execution across the company. This role is expected to evolve in scope as the enterprise data platform matures, with increasing influence across business domains and enterprise technology strategy.

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

Nice To Haves

Experience in manufacturing, aerospace, or hardware-driven environments
ERP/MES/PLM integration experience
Experience scaling data platforms in mid-stage growth companies
Exposure to data governance frameworks and metadata management
Experience evaluating cloud data platform evolution strategies

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