12+ years in data architecture, engineering, or analytics architecture.
Experience delivering enterprise-scale semantic layers or governed data products.
Proficiency in leading requirements workshops with SMEs and presenting to senior leadership.
Expertise in lakehouse and cloud-based platforms, especially Databricks and Delta Lake.
Strong knowledge of semantic layers, dimensional modeling, and data governance disciplines.
Hands-on experience with ontologies, knowledge graphs, and vector databases.
Responsibilities
Design and develop metrics layers, ontology frameworks, and business glossaries.
Evaluate data readiness across various dimensions including quality and usability.
Translate business rules from SMEs into scalable models.
Define standards for data lineage and entitlement frameworks.
Establish agent identity requirements for data governance.
Benefits
Opportunity to work with cutting-edge AI and data technologies.
Collaborative environment with cross-functional teams.
Professional development opportunities in advanced data architecture.
Exposure to innovative projects in automotive and supply chain domains.
Full Job Description
Function
Cloud & Data Engineering
Role Summary
We are seeking a Data and Context Architect to design the semantic, knowledge, and governance layers that enable AI agents to operate on trusted, well-structured, and governed data assets.
Key Responsibilities
Design and develop the metrics layer, ontology framework, search indexes, and business glossary.
Establish and evaluate data readiness across dimensions such as scope, freshness, semantic clarity, quality, governance, usability, and operational effectiveness.
Elicit business rules from SMEs and translate them into reusable, governed, and scalable models.
Define entitlement frameworks, data lineage standards, and agent identity requirements.
Required Technical Skills
Expertise with lakehouse and cloud-based data platforms, preferably Databricks, including Delta Lake, Unity Catalog, PySpark, or comparable technologies.
Strong knowledge of semantic and metrics layers, dimensional modeling, and domain-driven data modeling.
Hands-on experience with ontologies and knowledge graphs, including RDF/OWL, Neo4j, or similar property graph technologies.
Experience with vector databases, semantic search, embeddings, and Retrieval-Augmented Generation (RAG) architectures.
Deep understanding of data governance disciplines, including data lineage, access management, business glossaries, and master data management.
Experience with event-driven architectures and business rules implementation using technologies such as Kafka, Amazon MSK, alerting platforms, and rules engines.
Proficiency in data quality management, data reconciliation, and data readiness assessments.
Minimum Experience Required
12+ years of experience in data architecture, data engineering, or analytics architecture.
Proven delivery of at least one enterprise-scale semantic layer, knowledge graph, or governed data product.
Experience leading requirements workshops with business subject matter experts (SMEs) and developing architectural recommendations for senior leadership and stakeholders.
Preferred Skills
Domain experience in automotive, manufacturing, or supply chain environments.
Exposure to GenAI grounding techniques, text-to-SQL solutions, and natural language analytics platforms.
Professional certifications in Databricks, cloud architecture, or data architecture.
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About Hitachi America
Hitachi America is a subsidiary of Hitachi, Ltd., a Japanese multinational conglomerate. They provide a wide range of products and services, including information technology, power systems, and social infrastructure. They work with clients in a variety of industries, including healthcare, transportation, and finance. They are committed to sustainability and social responsibility, and have implemented various initiatives to reduce their environmental impact.
