Platform: OCI/AIDP and/or Databricks

Role Overview
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.
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.

Key Responsibilities
· 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.

Required Skills
· 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.

· 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.

Principal Data Platform & AI Architect

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