Lead Data Engineer
Compunnel
We are seeking a Lead Data Engineer with 10–12+ years of experience to design, build, and optimize modern enterprise data platforms and AI-enabled data solutions. This hands‑on individual contributor role focuses on developing scalable data ecosystems, enabling AI-driven data access, and delivering intelligent data solutions using Microsoft Fabric Data Agent/Fabric IQ or Databricks Genie. The ideal candidate will possess strong expertise in data engineering, cloud data platforms, and AI/LLM technologies. Key Responsibilities Design, build, and optimize enterprise-scale data platforms and modern data lake architectures. Implement, configure, and support Microsoft Fabric Data Agent/Fabric IQ or Databricks Genie solutions. Enable AI-driven data access and develop data foundations for Agentic AI use cases. Configure and optimize data agents, retrieval systems, and AI-powered data workflows. Design, develop, and maintain scalable data pipelines, ingestion frameworks, and ETL/ELT processes. Build and optimize data transformation workflows to support enterprise analytics and AI initiatives. Collaborate with AI, analytics, and business teams to deliver intelligent, data-driven solutions. Ensure data quality, governance, security, scalability, and performance across enterprise data platforms. Evaluate and implement modern data engineering best practices, tools, and emerging technologies. Lead technical solution design, development, testing, and production deployment with minimal supervision. Troubleshoot and optimize data platform performance and reliability. Required Qualifications 10–12+ years of professional experience in Data Engineering. Strong hands‑on expertise with modern cloud data platforms and enterprise data architectures. Experience implementing Microsoft Fabric Data Agent/Fabric IQ or Databricks Genie. Strong knowledge of Artificial Intelligence (AI), Large Language Models (LLMs), and configuring data agents for AI‑powered solutions. Experience building or enabling AI agents on enterprise data platforms and data lake environments. Strong experience designing and developing data pipelines, ETL/ELT processes, and data transformation frameworks. Experience with data modeling and enterprise analytics platforms. Strong understanding of enterprise data governance, security, and performance optimization. Ability to independently drive technical initiatives from architecture and design through production deployment. Excellent analytical, problem‑solving, communication, and collaboration skills. Preferred Qualifications Experience with Microsoft Fabric, Azure Data Services, Databricks, and modern lakehouse architectures. Experience with Agentic AI, Retrieval‑Augmented Generation (RAG) architectures, vector databases, or AI‑driven analytics solutions. Experience implementing scalable cloud‑native data engineering solutions and enterprise AI platforms. #J-18808-Ljbffr
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