Sr Lead Architect

Area(s) of responsibility

We are looking for a highly experienced <strong>Data Architect (Grade 7A)</strong> to lead the design and delivery of the enterprise Data & Insights platform on <strong>Microsoft Azure</strong>. The role demands deep expertise in <strong>cloud data architecture</strong>, <strong>data models</strong>, <strong>data lake/lakehouse</strong>, <strong>vector-store based RAG systems</strong>, <strong>GenAI</strong>, <strong>Agentic AI</strong>, and governance using <strong>Microsoft Purview</strong>. The ideal candidate has strong hands-on skills in <strong>Python</strong>, <strong>LangChain</strong>, <strong>LangGraph</strong>, Azure data services, and end-to-end SDLC execution.

Roles & Responsibilities

• Architect and design Azure-based <strong>data lake/lakehouse platforms</strong>, domain data models, and ingestion-to-consumption pipelines.
• Develop conceptual, logical, and physical <strong>cloud data models</strong> aligned with enterprise standards.
• Architect <strong>RAG pipelines</strong> including embeddings, chunking, vector stores, hybrid retrieval, reranking, and evaluation.
• Build <strong>Agentic AI workflows</strong> using LangChain and LangGraph; design tool orchestration, memory, and safety layers.
• Implement governance with <strong>Microsoft Purview</strong> for cataloging, lineage, PII tagging, and policy enforcement.
• Ensure platform security using Entra ID, private endpoints, VNETs, Key Vault, and encryption controls.
• Lead solution architecture reviews, performance tuning, cost optimization, and NFR engineering.
• Oversee CI/CD (Azure DevOps), IaC (Terraform/Bicep), and observability (Azure Monitor, App Insights).
• Mentor engineering teams and standardize best practices, patterns, and reusable components.

Technical Skills

<strong>Mandatory</strong>

• <strong>Azure Data Platform</strong>: ADLS Gen2, Synapse/Serverless SQL, Databricks/Spark, ADF/Synapse Pipelines
• <strong>Programming</strong>: Python, PySpark, SQL
• <strong>GenAI & Agentic AI</strong>: RAG architecture, vector stores (Azure Cognitive Search, Pinecone, Weaviate, Qdrant), embeddings, reranking
• <strong>Frameworks</strong>: LangChain, LangGraph
• <strong>Data Modeling</strong>: Conceptual/logical/physical models, Delta/Parquet patterns, lakehouse modeling
• <strong>Data Governance</strong>: Microsoft Purview (catalog, lineage, classification, glossary, PII governance)
• <strong>Security</strong>: Entra ID, RBAC/ABAC, Key Vault, VNET integration, encryption
• <strong>SDLC & DevOps</strong>: Azure DevOps (CI/CD), Terraform/Bicep, ADRs, HLD/LLD documentation
• <strong>Performance & Cost Optimization</strong> across compute, storage, vector workloads, and pipelines

<strong>Preferred</strong>

• Azure Fabric / OneLake; Power BI semantic modeling
• dbt for transformations and testing
• Cosmos DB, PostgreSQL, SQL Server MI
• Knowledge graphs (Neo4j) and graph-based retrieval
• LLMOps: evaluation, telemetry, safety assessment, drift monitoring
• FinOps optimization practices
• Multi-cloud experience (AWS/GCP equivalents)
• API design: REST, GraphQL, gRPC

Qualifications

• Bachelor’s or Master’s degree in Engineering, Computer Science, or related discipline.
• 12–14 years of total experience with <strong>minimum 5+ years</strong> in cloud data architecture.
• Proven experience delivering <strong>Azure-based</strong> data platforms and production-grade <strong>GenAI/RAG systems</strong>.