Principal Data Architect
Location: Menlo Park, CA(Remote)
Position Overview: We are looking for a forward thinking 10+ Years Data Architect, who is visionary to pioneer the engineering and orchestration of an enterprise-scale, Self-Healing Data Fabric. In this high-impact mandate, you will dismantle traditional, rigid ETL pathways and help implement an intelligent "nervous system" framework where operational metadata is continuously active, enterprise data governance is completely computational, and multi-party data virtualization relies on zero-copy architectures. Mandatory Technical: Active Metadata Infrastructure: Demonstrated success designing closed-loop data automation pipelines (e.g., building automated engines for metadata-triggered schema self-repair and structural drift remediation). Advanced Semantic Engineering: Comprehensive mastery of semantic web standards, including RDF, OWL, and SHACL, for building ontology-first structural data models alongside SPARQL for context-aware graph reasoning. Policy-as-Code Compliance: Production-grade deployment experience utilizing Open Policy Agent (OPA) or equivalent zero-trust policy engines to enforce programmatic, contextual data access control layers. Caelum or Amundsen push-events: Alongside DataHub's Actions Framework to drive real-time, event-based data quality orchestration and automated schema rollbacks
Note:
Target Educational Profiles: Required: Minimum of 10+ years of enterprise data strategy experience. Preferred: Master's degree or Ph.D. in Computer Science with a core focus on Formal Methods/Symbolic Logic or Computational Mathematics. Key Focus Areas: Active Metadata, RDF, OWL, SHACL, SPARQL, OPA, Caelum/Amundsen.
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