Max Pay Rate - $53.03/hr on W2 Title: Microsoft Azure Data Engineer

Must Have Technical/Functional Skills: •8+ years in data engineering with cloud-native architecture. [Azure] •Hands-on experience with Microsoft Fabric components (Data Factory, OneLake, Lakehouse, Power BI, KQL). •Strong skills in SQL, Python, DAX, and Spark/Python development. •Experience with Azure OpenAI, Copilot, and LLM integration. •Familiarity with containerization (Docker), Azure Container Apps, and DevOps tools. •Strong communication and documentation skills

Preferred Certifications if any: •Microsoft Certified: Azure Data Engineer Associate •Microsoft Certified: Azure AI Engineer Associate •Microsoft Certified: Fabric Analytics Engineer Associate •Microsoft 365 Certified: Enterprise Administrator Expert

Primary Responsibilities: •Architect end-to-end Microsoft Fabric solutions including Data Factory, OneLake, Lakehouse, and real-time analytics platforms. •Design and deploy AI models using Azure AI Foundry and Azure OpenAI Service. •Implement Microsoft Copilot solutions across the Microsoft ecosystem, integrating with Fabric data sources. •Build and troubleshoot data pipelines from diverse sources (SQL, APIs, Salesforce, Oracle, Dynamics) using. •Optimize semantic models and implement medallion architecture (bronze, silver, gold). •Develop real-time streaming analytics using Event Streams and KQL databases. •Monitor performance using Fabric Capacity Metrics and resolve ingestion or modeling issues. •Plus Point - Build and require hands-on experience on Databricks platform - [Cherry on cake]

AI & Advanced Analytics: •Customize and implement Microsoft Copilot solutions (e.g., Copilot for Power Platform, Fabric). •Work with GPT models and prompt engineering via Azure OpenAI Service. •Build RAG (retrieval augmented generation) pipelines and hybrid search architectures. •Ensure responsible AI practices and governance. Governance & DevOps - Plus point •Establish data governance frameworks using Microsoft Purview and Fabric governance tools. •Implement CI/CD pipelines and DevOps practices for data and AI solutions. •Manage RBAC and zero-trust security across workspaces. Consulting & Leadership - Plus Point •Lead discovery sessions and client engagements to understand requirements. •Translate technical concepts into financial business value propositions. •Conduct workshops, knowledge transfers, and post-implementation support. •Mentor junior engineers and contribute to enterprise AI strategy

Generic Managerial Skills, If any: - Lead a Team of 3-5 developers. - Follow Scrum practices to lead team and manage deliveries.

Key Words to search in Resume: - Azure Data Engineer, - AI models using Azure AI Foundry and Azure OpenAI Service. - Databricks, - DevOps.