Rahul Agarwal — VP of Engineering

As a senior leader in Data Engineering and AI, I bring 17+ years of experience delivering enterprise-grade data platforms, ML solutions, and GenAI automation across global markets. At Walmart, I’ve led hybrid teams of data engineers and scientists to deploy scalable systems — from Spark-based data lakes to LLM-powered conversational agents. My recent work includes building a RAG-based GenAI chatbot for Walmart’s International Data Lake using LangChain and OpenAI, and an Agentic AI that auto-generates ingestion prompts and discovers data feeds. I also developed a GenAI-powered SQL validator using Spark logs, reducing QA cycles by 70%. With deep expertise in cloud platforms (GCP, Azure), MLOps, Airflow, CI/CD, and data governance, I specialize in scaling systems, optimizing cost ($2M+ savings), and aligning platform roadmaps with business OKRs. I’m passionate about mentoring teams and driving AI innovation that translates into real business impact. Key Highlights from My Profile: Strategic Vision: I've made impactful contributions to annual budgeting, LRAP, and resource planning, while effectively prioritising goals for the International Data organisation. Customer 360 platform (30% CRM targeting improvement) Collaborative Excellence: My collaborations span cross-functional partnerships, professional services, analytics teams, and engineering groups. Together, we've crafted, designed, and executed cutting-edge solutions that drive innovation. Customer-Centric Innovation: Guiding the design and execution of a revolutionary Omni-channel product, the Unified Customer View, across three countries, I've not only elevated technical excellence but also mentored engineering associates in the realms of technology, analytics, and business skills. Cloud Migration Mastery: In devising and implementing intricate GCP and Azure IaaS/PaaS solutions, I've facilitated the seamless migration of data from on-premises systems to GCP/Azure across seven international markets. Streamlined Data Flow: I've engineered a robust streaming framework, ensuring real-time data ingestion into the Data Lake. This framework introduces a multitude of source/target connectors, transformations, reconciliation, and cutting-edge features. combine 2 sections Efficiency Pioneer: My contributions extend to the design and development of an advanced data ingestion CI/CD/DevOps solution, effectively optimising the efficiency International Lake pipelines. GenAI Automation – RAG chatbot + Agentic AI for International Data Lake GenAI Data Validation Assist – SQL auto-generation from Spark logs

Stackforce AI infers this person is a Data Engineering and AI expert in the SaaS industry.

Location: Bengaluru, Karnataka, India

Experience: 15 yrs 10 mos