I go beyond building data pipelines! As a Data & AI Engineer, I not only create end-to-end data pipelines but also build intelligent systems that make data truly useful — enabling smarter decisions, actionable insights and automated workflows. Grounded in data engineering, I design and optimize modular ETL workflows on Azure and Databricks, enforcing data quality and governance, handling PII securely, and building reliable data models. With expertise in Delta Lake, Lakehouse architectures and performance tuning, I ensure pipelines are not just functional, but efficient, cost-effective and built for scale. My work empowers AI and analytics teams to access high-quality datasets with complex business transformations using PySpark and SQL. Building on this foundation, I’ve also ventured into the AI side — developing multiple Generative AI PoCs that extend the value of data engineering. Leveraging Neo4j knowledge graphs, RAGs, AI agents, and frameworks like LangChain and LangGraph, I’ve built systems ranging from an agentic data ingestor to a marketing assistant integrated with knowledge graphs. These projects reflect my ability to go beyond providing data, developing intelligent systems that generate actionable insights and streamline operations. I’m passionate about continuous learning and making an impact, whether through innovative data solutions or community engagement. From leading 500+ tech enthusiasts at Devs' Street, to hosting tech events with Google, and managing internal tech communities and workshops at MathCo, I thrive in environments that foster knowledge sharing, collaboration, and innovation. What sets me apart is a relentless drive to create impact, keeping me consistent in learning, building and contributing. I enjoy discussing emerging technologies, collaborating on meaningful projects and exploring new opportunities—let’s connect!