Data Analyst,Business Intelligence,Business Analyst, Reporting Analy

K Rohith Kumar

Data Analyst Business Intelligence Analyst Location: Hyderabad, India (Open to Remote) Email: **********.*******@*****.*** Phone: +91-891******* LinkedIn: linkedin.com/in/krohith

Professional Summary

Mid-Level Data Analyst SQL & Reporting Specialist with 3 years of hands on experience in data analytics and business intelligence. Proficient in SQL, Advanced Excel, Power BI, Tableau, and Python for data modeling, visualization, and automation. Proven ability to collect, clean, and analyze large datasets to extract actionable insights and drive data-driven decision making. Adept at creating interactive dashboards and reports, identifying trends and patterns, and collaborating with cross-functional stakeholders (including data engineers and business users) to meet business objectives. Excellent communication and documentation skills with a track record of presenting complex findings to non-technical stakeholders and working in Agile, fast-paced environments. Open to mid-level Data Analyst / BI roles in remote or Hyderabad-based positions.

Technical Skills

● Data Analysis & Visualization: SQL (complex queries, joins, subqueries), Excel

(PivotTables, VLOOKUP, advanced formulas), Power BI (DAX, Power Query), Tableau, Data Modeling (star schema design, dimensions/facts), Data Manipulation

● Programming & Scripting: Python (Pandas, NumPy, Matplotlib) for data cleaning, analysis and automation; basic R knowledge

● Database & Big Data: Databricks (Spark), Azure SQL Database, SQL Server; experienced in ETL processes and handling large datasets

● Tools & Platforms: Azure Data Services (Azure Databricks, Azure Data Factory), AWS

(S3, Redshift) basics, Visual Studio Code, JIRA (Agile), Git version control

● Soft Skills: Requirements gathering, stakeholder communication, documentation, teamwork & collaboration, attention to detail, problem-solving, presentation skills

,Reporting Automation & Dashboarding, Cross functional Stakeholder Collaboration, Actionable Business Insights & Strategic Recommendations. Familiar with SOP documentation, internal audit procedures, and driving quality process improvements in cross-functional settings.

● Modern Stack Familiarity: dbt (data build tool), Airflow (workflow orchestration), Azure / Power BI Service (cloud BI deployment)

Professional Experience

Quality Specialist– Amazon (Hyderabad, India) Nov 2023 – August 2025

● Data Analytics & Reporting: Utilize SQL and Python to extract and analyze large-scale e-commerce data (millions of rows across multiple tables) for trends in customer behavior and operational performance. Created complex SQL queries and stored procedures to generate datasets for analysis, ensuring accuracy and integrity of data.

● Interactive Dashboards: Develop and maintain interactive dashboards in Power BI to track key performance indicators (KPIs) such as sales revenue, order fulfillment rates, and customer satisfaction metrics. Implemented advanced DAX measures and data modeling in Power BI to enable dynamic slicing of data and drill-down analysis.

● Business Insights: Translate data findings into actionable business insights – e.g., identified a drop in conversion rates for a product category and alerted product teams, contributing to a 15% improvement in sales after corrective actions.Delivered 10+ ad-hoc reports monthly that enabled marketing and operations teams to quickly adjust campaigns, improving response time by 15%.

● Stakeholder Collaboration: Collaborated with 5+ cross-functional teams to refine data requirements, reducing report rework by 25% and accelerating project timelines . Presented monthly insights and dashboard updates to senior management, communicating complex analyses in clear, concise terms which improved stakeholder understanding of business metrics.

● Process Optimization: Automated recurring reporting tasks by creating SQL-driven pipelines and Excel macros, reducing manual effort by 30% and ensuring timely delivery of reports. Coordinate with data engineering teams to integrate new data sources (e.g., AWS S3 logs) into the analysis pipeline. Created and maintained comprehensive documentation that decreased onboarding time for new analysts by 40% and reduced reporting errors.

● Conducted quality assurance checks and root cause analysis on operational datasets to identify compliance gaps and reporting discrepancies, ensuring adherence to internal audit standards.

Associate Engineer– Allstate (Hyderabad, India) Jul 2021– Nov 2022

● Data Exploration & ETL: Collected, cleaned, and analyzed insurance data (policy and claims databases) using SQL and Excel. Performed ETL processes to merge data from multiple systems (claims, underwriting, customer service) into a centralized repository, ensuring data quality and consistency. Mapped data from legacy formats to new database schemas, contributing to a successful data migration for a new claims management platform.

● Dashboarding & Visualization: Built interactive reports and dashboards using Tableau and Power BI to visualize key insurance metrics (claim volumes, loss ratios, customer retention rates). Enabled teams to monitor trends and identify anomalies (e.g., spike in claims for a region) in real-time. One dashboard on claims turnaround time helped operations managers reduce processing delays by 10% through targeted process changes.

● Insights & Decision Support: Analyzed trends and patterns in claims and customer data to support business decisions. For example, conducted a deep-dive analysis of auto insurance claims data that uncovered high-frequency incident spots; this insight informed a new risk mitigation strategy, potentially reducing claim costs. Prepared clear summary reports and presentations to communicate findings to underwriting and risk teams, facilitating data-driven policy adjustments.

● Stakeholder Engagement: Worked in Agile teams to deliver 3+ data products quarterly, improving stakeholder satisfaction and delivery speed. Gathered and validated requirements for new reports and data requests by working directly with stakeholders from different departments (Actuarial, Sales, Operations). Regularly coordinated with the IT team to resolve data discrepancies and implement enhancements. Maintained documentation (data dictionaries, report guides, process notes) to support data governance and ensure stakeholders could trust and understand the analytics outputs.

● Tools & Achievements: Leveraged Azure Databricks to run PySpark notebooks for large-scale data processing on claim datasets, improving analysis turnaround time by 20%. Utilized advanced Excel techniques and Python scripting to identify and reconcile data discrepancies between source systems, improving data accuracy for reporting. Received formal commendation from management for improving data accuracy and clear communication, leading to adoption of new reporting standards. Projects

Retail Sales Analysis Dashboard – Self-initiated end-to-end data analytics project (2024)

● Objective: Analyze retail sales data and create a business intelligence dashboard to provide insights into sales performance and customer behavior.

● Data & Tools: Worked with a dataset of 1.2 million sales records (product, store, and customer details). Used SQL for extensive data extraction and transformation – writing complex queries and joins to aggregate sales by region, product category, and time period. Cleaned and prepared the data using Python (Pandas) for consistency and completeness.

● Dashboard Development: Imported the prepared data into Power BI and designed an interactive dashboard. Implemented data modeling with proper relationships (star schema: fact sales table with dimension tables for Date, Product, Store, Customer). Created DAX measures for KPIs like Total Sales, Year-over-Year Growth, Top 10 Products by Revenue, and Customer Lifetime Value. Utilized Power BI visuals to highlight trends (line charts for monthly sales trends, bar charts for category performance, geo-maps for regional sales distribution).

● Business Insights: The dashboard revealed meaningful insights for example, identified that Region A had the highest growth in Q3, driven by an increase in Product X sales, whereas Region B lagged due to lower customer retention. Presented these findings as if to a stakeholder, recommending targeted marketing campaigns in underperforming regions and stock adjustments for high-demand products. This project demonstrates the ability to derive actionable business insights from data using SQL and Power BI, similar to real-world scenarios. (Project completed and documented in a report and presentation format.)

Education

Bachelor of Technology in Computer Science and Engineering – JNTUH 2019

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