Sravan Kumar is a Senior Data Scientist and Data Engineer with 13 years of experience building enterprise-scale Microsoft Azure data platforms and lakehouse architectures that power analytics, ML, and GenAI applications. He specializes in Azure Databricks, Delta Lake, Synapse, ADF, and end-to-end PySpark pipeline optimization—delivering 40–70% runtime reductions and measurable compute savings while modernizing on-prem SQL/SSIS estates to cloud-native solutions. Sravan designs Medallion lakehouses, governed data assets, and LLM-ready ingestion pipelines (RAG, chunking, embeddings, vector indexing) that address the real failure mode of AI projects: unreliable data. He has delivered hundreds of automated pipelines and integrations for large enterprises like Shell and HP, combining hands-on engineering with pragmatic data governance. Based in Houston and completing a Master’s in Computer Science, he’s seeking senior roles focused on Microsoft-centric stacks or teams building production GenAI products. An analytical tinkerer by nature, he turns messy multi-TB feeds into trusted datasets that analysts, models, and LLMs can rely on.
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