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The Data Architect will lead the design and evolution of enterprise data architecture to support strategic business initiatives, including AI enablement, analytics modernization, and data governance. This role will define and enforce architectural standards, ensure scalable and secure data solutions, and partner across business and technology teams to align data capabilities with enterprise goals. A strong emphasis is placed on building knowledge-graph–driven architectures and leveraging modern platforms such as Databricks Unity Catalog, Neo4j, and ArangoDB (preferred) to support next-generation data intelligence.

Essential Duties and Responsibilities

• Define and maintain enterprise data architecture blueprints, including relational, graph, and semantic data models, integration patterns, and metadata standards.
• Lead the design of scalable, secure, and high-performing data platforms—spanning lakehouse, graph, and operational databases—to support analytics, AI, and enterprise applications.
• Establish architectural guardrails for data movement, storage, cataloging, and governed access across cloud and on-premises environments, including governance frameworks using Databricks Unity Catalog.

• Collaborate with data engineers, analysts, and business stakeholders to translate business requirements into robust data solutions, including knowledge graph architectures.
• Ensure alignment with data governance, privacy, and security standards, ensuring automated lineage, access control, and policy enforcement.
• Guide the selection and implementation of technologies such as Neo4j, ArangoDB (preferred for multi-model graph workloads), and cloud-native platforms including Databricks.

• Lead data architecture components of application modernization efforts, including migration from legacy systems to cloud-native and graph-enabled architectures.
• Design data services, graph APIs, and event-driven data flows to support microservices, distributed systems, and modern containerized workloads.
• Partner with application architects to ensure data strategies—including knowledge graph integration—align with modernization roadmaps and performance needs.

• Evaluate emerging technologies and trends in graph databases, semantic layers, metadata platforms, and AI/ML tooling to inform architectural decisions.
• Support development of reusable enterprise data assets, including canonical models, knowledge graphs, semantic layers, and governed datasets in Unity Catalog.
• Mentor engineering and analytics teams on best practices in modern data architecture, graph modeling, multi-model databases, and metadata-driven development.

• Partner with product, analytics, and engineering teams to ensure architectural consistency and delivery excellence across the enterprise.
• Serve as a thought leader and advocate for data-centric and graph-centric design practices.
• Contribute to the development of a modular, agentic data architecture that supports human-in-the-loop validation, AI-driven workflows, and enterprise knowledge integration.

Required Skills and Qualifications

• 8+ years of experience in data architecture, data engineering, or enterprise architecture roles.
• Proven expertise in designing and implementing modern data platforms (e.g., data lakes, lakehouses, data mesh architectures).
• Hands-on experience with Databricks, including Unity Catalog for data governance, lineage, and access control.
• Strong experience with knowledge graphs, semantic modeling, and graph database technologies. Preferred: ArangoDB (multi-model graph/document/key-value). Highly Desired: Neo4j and Cypher query language.
• Deep knowledge of data modeling (conceptual, logical, physical), metadata management, data lineage, and ontology/semantic layer development.
• Strong command of SQL, ELT/ETL processes, and cloud-native data services (Azure Data Factory, Databricks, Snowflake, Synapse, etc.).
• Experience with data governance, privacy, and security frameworks (HIPAA, GDPR, data classification models).
• Familiarity with AI/ML data pipelines, feature engineering, model monitoring, and integration with enterprise knowledge graphs.
• Ability to communicate complex architectural concepts to both technical and non-technical stakeholders.
• Experience working in Agile or hybrid delivery environments.
• Bachelor’s or Master’s degree in Computer Science, Information Systems, or related discipline (or equivalent experience).