Data & AI Architect – Azure, Microsoft Fabric, Databricks

Role: Data & AI Architect – Azure, Microsoft Fabric, Databricks
Exp: 12+ Years
Location: BLR (Client Location)
Mandatory: Microsoft Fabric (OneLake, Lakehouse, Warehouse, Data Factory), Azure Databricks (Spark, Delta Lake, Unity Catalog), Azure Data Factory, Azure Data Lake, Synapse, Power BI, Data Governance (Purview, Unity Catalog, RBAC), AI/ML/GenAI Architecture (RAG, LLM, Embeddings, Vector Search)
Key Responsibilities:
Design end-to-end enterprise data architectures (Fabric, Databricks, ADF, Data Lake, Synapse)
Translate business requirements into scalable, secure data architecture & solution designs
Define architecture patterns for ingestion, transformation, storage, processing, serving, analytics, reporting
Design Lakehouse, Data Warehouse, Medallion Architecture solutions
Design AI/ML-ready data architectures (ML, GenAI, RAG, embeddings, vector search)
Integrate AI agents with APIs, databases, cloud services (AWS/Azure), enterprise apps
Define Fabric architecture (OneLake, Lakehouse, Warehouse, Data Factory, Dataflows, Power BI)
Design Databricks/Delta Lake architectures (Spark, Structured Streaming, Unity Catalog)
Define Bronze/Silver/Gold data-layer strategies
Design ETL/ELT patterns (ADF, Fabric Data Factory, Databricks)
Define data models (conceptual, logical, physical), dimensional models, star schemas
Define data governance & security (Purview, Unity Catalog, RBAC, lineage, auditing)
Optimize performance, scalability, cost (Databricks/Spark, Delta Lake, Fabric, SQL, Power BI)
Design cloud solutions (Azure primary, AWS/GCP knowledge)
Participate in RFPs, sales proposals, technical estimates
Requirements:
12+ years in Data Architecture (Azure, Fabric, Databricks, ADF, Data Lake, Synapse, Power BI)
Strong Fabric & Databricks architecture (OneLake, Lakehouse, Warehouse, Data Factory, Dataflows, Power BI, Spark, Delta Lake, Unity Catalog)
Medallion Architecture, Bronze/Silver/Gold data layers
ETL/ELT, CDC, SCD Type 1/2, incremental loads, reconciliation
Data modeling (conceptual/logical/physical, dimensional, star schemas)
Data governance & security (Purview, Unity Catalog, RBAC, masking, encryption, lineage)
Performance & cost optimization (Databricks/Spark, Delta Lake, Fabric, SQL, Power BI)
Cloud architecture (Azure primary, AWS/GCP knowledge)
AI/GenAI architecture (RAG, LLM, embeddings, vector search, AI agents)
Strong technical leadership, stakeholder management, architecture documentation
CI/CD, DevOps, IaC, monitoring, deployment strategies knowledge

Work arrangement
Hybrid