Full Time Only: Azure Data Solutions Architect – Databricks

Job Title: Azure Data Solutions Architect – Databricks Location: Newtown Square, PA (Hybrid — 3 days onsite per week) Employment Type: Full-time Role Overview We are seeking an experienced Azure Data Solutions Architect with deep Databricks expertise to design, deliver, and govern enterprise-scale data platforms. In addition to core lakehouse responsibilities, this role will lead design and delivery of Agentic AI and LLM-powered solutions, including retrieval-augmented generation (RAG), grounded copilots, and autonomous data workflows. The architect will own architecture and best practices across Azure, Databricks, ADF, Synapse, Fabric, and Unity Catalog—partnering with engineering, product, and security teams to enable analytics, BI, ML, and GenAI use cases. Key Responsibilities Azure certifications (e.g., Microsoft Certified: Azure Solutions Architect, Azure Data Engineer). Prior enterprise experience deploying lakehouse or hybrid lake/warehouse architectures. Experience with streaming solutions (Event Hubs, Kafka) and real-time processing in Databricks. Familiarity with BI tools (Power BI, Looker, Tableau) and how data models serve reporting/analytics. Experience with cost management and governance in large Azure environments. Hands-on experience with Azure OpenAI Service and orchestrating LLM apps using Azure AI Studio Prompt Flow, LangChain, or Semantic Kernel. Practical RAG implementation at scale: embedding model selection, chunking strategies, hybrid/vector search, reranking, and retrieval evaluation. Experience with vector databases/indexes in Azure ecosystems (e.g., Azure AI Search vector, Databricks Vector Search) and integration with Delta Lake sources. Proficiency with Databricks MLflow, Unity Catalog model registry, and model/prompt artifact versioning and lineage. Experience building agentic workflows with tool/function calling, task planning/execution, and safe tool boundaries. Knowledge of Responsible AI practices: safety policies, content filtering, PII handling, prompt injection defenses, red-teaming, and governance aligned to enterprise controls. Experience operationalizing LLM apps: observability, evaluation frameworks, CI/CD for prompts/models/retrievers, token/cost management, and SLOs. Show more Show less