Data Analyst Power Bi

Summary

Sai Sreeja Eegalapati Data Analyst

***************@*****.*** +1-470-***-**** Marietta, GA LinkedIn Data Analyst with 3+ years of experience in delivering data-driven business solutions through advanced analytics, predictive modeling, and visualization. Adept at Python, R, SQL, Tableau, and Power BI, with expertise in big data processing, feature engineering, and cloud computing. Skilled in transforming complex datasets into actionable insights that optimize business performance, increase revenue, and drive strategic decision-making. Highly collaborative and adaptable, with a track record of working in cross-functional teams across finance, marketing, and operations to implement data solutions that reduce costs and enhance operational efficiency.

Technical Skills

• Programming & Query Languages: Python, R, SQL, DAX

• Data Analytics & Big Data Technologies: NumPy, Pandas, Apache Spark (PySpark), Hadoop, Apache Hive, Apache Kafka, Airflow, Snowflake, BigQuery

• Databases & Data Warehousing: MySQL, PostgreSQL, MongoDB, Oracle, MS SQL Server, NoSQL

• Data Visualization & Reporting: Power BI, Tableau, Google Analytics, Seaborn, Matplotlib

• Machine Learning & AI: TensorFlow, Keras, Sci-kit Learn, Predictive Modeling, Feature Engineering

• Cloud & DevOps Tools: AWS, Azure, GCP, Docker, Jenkins, Databricks, CI/CD Pipelines

• Project Management & Agile Tools: JIRA, Scrum, Kanban Professional Experience

Data Analyst, Epsilon 02/2024 – Present Remote, USA

• Designed and implemented automated data pipelines using Python & SQL, reducing manual data processing efforts by 40% and enabling real-time analytics.

• Developed and optimized complex SQL queries, reducing execution time by 30%, improving data accessibility for business intelligence and decision-making. Leveraged Google Analytics & Tableau to create insightful dashboards, increasing stakeholder engagement by 35%.

• Led the creation of interactive Tableau dashboards, providing data visualizations that enhanced stakeholder engagement by 35% and helped drive revenue growth. Enhanced data quality by 25% through rigorous validation & cleansing, ensuring accuracy in business decisions.

• Conducted statistical analysis and predictive modeling to forecast customer behavior, increasing marketing campaign effectiveness by 25%. Optimized SQL queries, reducing execution time by 30%, improving data accessibility and reporting.

• Improved data quality and governance by implementing rigorous validation and cleansing techniques, enhancing data accuracy by 25%.

Graduate Research Assistant, Lincoln National Corp 01/2023 – 12/2023 Remote, USA

• Developed a real-time financial performance monitoring system, integrating 1M+ financial records using SQL and Python, improving financial forecasting accuracy by 20%.

• Designed and managed SQL schemas with over 60 tables and 15 complex joins, optimizing data normalization and reducing redundancy.

• Integrated 10TB+ of financial data into Snowflake using AWS Glue & Redshift, allowing for scalable and efficient financial reporting.

• Built Power BI dashboards that consolidated data from 12+ sources, implementing 20+ dynamic visualizations with advanced filters and slicers to support business strategy.

• Used machine-learning models in Python to analyze historical financial data, enabling predictive analytics that reduced risk assessment errors by 18%.

Data Analyst, Genpact 06/2020 – 07/2022 Hyderabad, India

• Developed and implemented a Customer Purchase Analysis and Reporting System, providing insights into consumer behavior, purchasing patterns, and product preferences, increasing targeted marketing efficiency by 20%.

• Designed and optimized SQL queries for data extraction and transformation, reducing processing time by 40% and improving data accessibility.

• Built predictive models using machine learning algorithms, increasing forecasting accuracy for customer demand and sales trends.

• Created Tableau dashboards to visualize key sales trends, revenue metrics, and product performance, leading to a 10% increase in sales through data-driven decisions.

• Used Python (Pandas, NumPy, Sci-kit Learn) to clean, transform, and analyze datasets, ensuring data consistency and report accuracy.

Education

Master of Science, Kennesaw State University 08/2022 - 12/2023 Marietta, GA Computer Science

Bachelor of Technology, Swarnandhra College of Engineering and Technology 06/2017 - 05/2021 A.P., India Information Technology

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