Data Architect (DataOps) - SME
About The Position
The Data Architect (SME) leads the design and management of the organization’s enterprise data environment, ensuring information is accurate, connected, and supports advanced analytics and AI. The role integrates traditional databases with modern data platforms and semantic and knowledge-graph technologies to provide meaningful insights and support better decision-making. The SME establishes data standards, enables secure data sharing, and collaborates with engineering and AI teams to maintain structured, governed, high-quality data. The position also involves work with an in-house custom-developed application and advanced AI, generative AI, and multi-model engineering, including multi-model and multi-modality orchestration. Work may involve air-gapped, hybrid, and on-premise operational environments, as well as UI, backend, and middleware engineering using TypeScript, React, Python, and other modern technologies.
Requirements
- Bachelor's degree required.
- Minimum of 10 years of experience in data architecture, data engineering, or related areas.
- Strong experience with enterprise data platforms, distributed systems, and modern data pipelines.
- Familiarity with semantic technologies (RDF, OWL, SPARQL), ontologies, and knowledge graph design.
- Experience with metadata management, data lineage, and data governance processes.
- Knowledge of cloud data services and secure, multi-environment data integrations.
- Ability to communicate complex technical concepts clearly to non-technical stakeholders.
- Experience with an in-house custom-developed application.
- Advanced AI, GenAI, and multi-model engineering, including multi-model and multi-modality orchestration.
- Provenance and end-to-end data lineage tracking.
- Experience with air-gapped, hybrid, and on-premise operational environments.
- UI, backend, and middleware engineering using TypeScript, React, Python, and other modern technologies.
Nice To Haves
- Experience supporting AI/ML teams, retrieval architectures, or vector-based search.
- Background working in secure, multi-enclave, or zero trust environments.
- Experience with streaming data, real-time processing, or hybrid cloud architectures.
- Advanced degree in Computer Science, Information Science, Data Engineering, or a related field.
Responsibilities
- Design and maintain enterprise data architectures that integrate multiple data systems.
- Build and manage knowledge graphs, ontologies, and metadata structures to improve data context and discovery.
- Develop secure, well-governed data pipelines and processes for high-quality, trusted data.
- Support AI and analytics teams by providing structured, contextual data for model development and retrieval workflows.
- Establish data governance, data quality, and metadata standards across the organization.
- Evaluate new technologies and recommend improvements to data platforms and processes.
- Ensure data sharing and access follow security, compliance, and zero trust requirements.
Benefits
- A wide variety of benefits; details are available through the company's benefits information.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
