Nikhil Kathuroju
Data Analyst @ Tata Consultancy Services
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United States
Information Technology & Services
Amazon Web Services (AWS), Microsoft Azure, Python (Programming Language), Data Architecture, Decision-Making, Reporting Requirements, Workday Reporting, Dashboards, Database Administration, Information Systems, Business Systems, SQL Server Reporting Services (SSRS), Communication, Agile Methodologies, Agile Project Management, Agile & Waterfall Methodologies, Linear Regression, Statistical Analysis, Data Research, Statistics
Experience

Data Analyst
● Designed and built a greenfield Azure Modern Data Platform to unify customer, sales, supply chain, inventory, e-commerce, and marketing data across 30+ countries, ingesting 25+ TB daily from 200+ source systems (SAP, Salesforce, Adobe Analytics, POS, Shopify, Google Analytics, Manhattan WMS). ● Developed and maintained enterprise-scale ELT pipelines using Azure Data Factory (ADF) Mapping Data Flows, Databricks, and Azure Functions to support customer 360, demand forecasting, personalization, and omnichannel analytics use cases. ● Architected and governed a multi-zone data lake on Azure Data Lake Storage Gen2 using Delta Lake (bronze → silver → gold), with automated partitioning, Z-ordering, and OPTIMIZE/VACUUM jobs reducing query costs by 42%. ● Built high-performance analytics solutions on Azure Synapse Analytics (dedicated + serverless pools) and Databricks SQL warehouses, powering 1,200+ concurrent users in Tableau and Power BI for merchandising, category management, and executive dashboards. ● Implemented near-real-time customer event processing using Azure Event Hubs, Stream Analytics, and Databricks Structured Streaming for cart abandonment, dynamic pricing triggers, and in-store beacon analytics. ● Created customer segmentation and propensity models by integrating Databricks Feature Store with MLflow and deploying scoring pipelines via Azure ML and ADF. ● Led full IaC implementation using Bicep, Azure DevOps YAML pipelines, and Terraform; enabled one-click promotion from Dev → QA → Prod with slot-based deployments and full rollback capability. ● Rolled out enterprise data governance using Azure Purview – automated scanning, data lineage, business glossary, PII classification, and sensitivity labeling across 1.8 billion weekly records. ● Established end-to-end data quality framework with Great Expectations, Monte Carlo (via Azure Functions), and custom ADF validation, achieving 99.98% SLA for critical revenue and inventory feeds.
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