Principal Data Platform & AI Architect-5

We are looking for a hands-on Data Platform Architect to design and drive an enterprise Lakehouse that supports analytics, data products, and Agentic AI use cases., * Design enterprise Lakehouse architecture, including ingestion, Medallion pipelines, storage, processing, serving, governance, security, and observability.

• Define scalable Bronze/Silver/Gold and AI-ready data layers for analytics and Agentic AI consumption.

• Design federated data-access patterns, including compute pushdown, caching, performance, and domain ownership.

• Establish data products, data contracts, metadata, lineage, data quality, schema evolution, and decentralized governance patterns.

• Design self-service data discovery, access, approval, lifecycle, archival, and entitlement workflows.

• Define automated schema evolution, mapping, CI/CD, asset bundling, and environment promotion patterns.

• Architect AI-ready data capabilities using semantic layers, knowledge graphs, vector stores, RAG/Graph RAG, and agent memory.

• Design MCP and A2A integration patterns connecting AI agents with enterprise data, applications, APIs, and workflows.

• Integrate platforms such as Informatica IDMC, ServiceNow, PostgreSQL, Oracle databases, CRM, Jira, Confluence, and IAM/Active Directory.

• Lead architecture discussions and align engineering, data, AI, governance, security, and business stakeholders through implementation.

This is not a high-level cloud or program architecture role. The ideal candidate must demonstrate strong design thinking, hands-on lakehouse architecture, data governance, and AI-ready data architecture, and be able to explain architectural decisions and trade-offs in depth. Strong Databricks/Lakehouse experience with some exposure to OCI/AIDP is acceptable; deep OCI expertise is not mandatory., * 12+ years in Data Architecture, Data Engineering, Cloud/Data Platform Architecture, or similar roles.

• Strong hands-on experience with Databricks and/or enterprise Lakehouse platforms.

• Deep understanding of Medallion Architecture, Delta Lake/Iceberg, Spark, data products, Data Mesh, and federated data architectures.

• Strong experience with data catalogs, metadata, lineage, data quality, data contracts, and governance.

• Experience with PostgreSQL, Oracle Autonomous Database/ADW, or comparable enterprise databases.

• Current hands-on understanding of Agentic AI, RAG, vector databases, knowledge graphs, semantic layers, and agent memory.

• Knowledge of MCP and A2A integration patterns.

• Experience with CI/CD, IaC, automated deployment, schema evolution, and environment promotion.

• Working knowledge of OCI and Oracle AIDP; strong Databricks candidates with some OCI/AIDP exposure are welcome.

• Excellent communication and architecture/design-thinking skills, with the ability to explain why a solution should be designed a particular way-not simply which tools to use.

Preferred

• Informatica IDMC / enterprise data catalog experience.

• ServiceNow and enterprise IAM integration experience.

• Neo4j or other graph database experience.

• Vector databases such as pgvector, Pinecone, Weaviate, or similar.

• Experience with LangGraph, Semantic Kernel, AutoGen, CrewAI, or similar Agentic AI frameworks.

• Experience working with regulated or enterprise-scale data environments.