Lithin Somavarapu

About Lithin Somavarapu

Analytical and detail-oriented Data Analyst with over 4 years of experience leveraging cloud platforms (Azure, AWS), SQL, and Python to design scalable data solutions, drive insights, and support business decision-making. Proven success in building and optimizing ETL pipelines, transforming raw data into actionable intelligence, and delivering high-quality dashboards and reports using Power BI, Grafana, and Tableau. Skilled in working across hybrid data environments including Microsoft Fabric, Databricks, Redshift, and S3, with a deep understanding of data modeling, performance tuning, and validation processes. Strong collaborator with experience partnering across engineering, DevOps, and business teams to translate complex data into strategic outcomes. Certified in Azure Data Engineering, Tableau, and Google Data Analytics, with a strong foundation in machine learning and statistical techniques.

Experience

1. Data Analyst

   Microsoft

   Feb 2024 — Present

   Developed and optimized data pipelines and ETL workflows using Azure Databricks, Microsoft Fabric, and SQL, supporting both real-time and batch analytics use cases with 99.9%+ reliability. Conducted deep-dive data analysis using Python (Pandas, NumPy) and SQL to uncover insights on system performance, data quality, and user behavior, influencing strategic decisions across engineering and product teams. Designed and maintained interactive dashboards and ad hoc reporting solutions to monitor data pipeline health, user metrics, and system KPIs, leveraging Power BI and Azure Monitor. Collaborated with stakeholders to define and refine analytical requirements, building scalable data models and visualizations to support business intelligence use cases. Led the migration of analytical workloads from Databricks to Microsoft Fabric, ensuring seamless transition, maintaining data quality, and aligning architecture with performance and cost-efficiency goals. Tuned Spark jobs and SQL transformations to reduce query times by 35%, improving the performance of dashboards and analytics applications. Integrated third-party APIs and internal microservices to enhance data availability for analytical workloads, ensuring clean, reliable, and well-documented data sources. Built and maintained CI/CD pipelines (Azure Pipelines, GitHub Actions) to supportautomated deployment of analytical scripts, ETL processes, and data validationworkflows. Ensured compliance and governance by implementing RBAC access models, auditlogging, and secure data handling practices across analytical environments.Authored clear documentation, including business logic, data dictionaries, and analyticsworkflows, improving collaboration across data, product, and software teams.Used Git and infrastructure-as-code tools to version and manage cloud resources,application configs, and deployment templates across development and production environments.

Education

• University of the Cumberlands

  Master's degree