Data Analytics Engineering

Nitya Rondla

*****.******@****.*** 408-***-**** San Jose, CA 95126

Education

Master of Science in Data Analytics, Data Engineering Specialization, San Jose State University Graduate Coursework: Data Analytics, DBMS, Data Visualization, Business Intelligence, Generative Model, Data Warehouse.

08/2024 – present

San Jose, United States

Bachelor of Computer Science, Marri Laxman Reddy Institute of Technology Relevant courses: Mathematics, Object Oriented Programming, Operating System, Data Mining, Cloud, Data Structures, Artificial Intelligence, Machine Learning, Data Engineering. 07/2018 – 08/2022

Hyderabad, India

Skills

Programming Languages

Python (Pandas, NumPy, Scikit-learn, Matplotlib, TensorFlow, PyTorch, OpenCV), Java, C, JavaScript

Web Development

HTML, CSS, JavaScript, MERN stack, Full-Stack Development Data Analysis & Visualization

Predictive Analytics, Data Preprocessing, Data Visualization

(Matplotlib, Seaborn, Tableau, Power BI)

Technologies

Tableau, Power BI, Firebase, Docker, Postman, AWS, MATLAB Data Engineering

Data Pipeline Development, ETL Processes, Data Cleaning and Transformation

Professional Experience

Data Engineer, Zensar Technologies

•Built ETL pipelines using Python and SQL, processing 100,000+ records daily and improving efficiency by 20%.

•Automated workflows to reduce pipeline processing time by 25%. 11/2022 – 07/2024

Hyderabad, India

•Modernized data systems with FIS, enhancing accessibility and integrating advanced analytics tools.

•Designed scalable SQL and NoSQL data models, supporting cross-functional analytics initiatives. Data Analyst Intern, Brilliant Technologies

• Designed Power BI dashboards for healthcare benchmarking, enhancing decision-making and transparency.

• Conducted sentiment analysis on CAHPS survey data to identify key drivers of patient satisfaction. 08/2022 – 10/2022

Hyderabad, India

• Leveraged Python and SQL for data cleaning, analysis, and visualization of large datasets.

• Delivered actionable insights through reports and visualizations, driving quality improvements in healthcare.

Projects

Data Insights Dashboard: Netflix [PowerBI, Google Collab, SQL]

•Processed and cleaned over 500,000 rows of raw data using Python, leveraging libraries like Pandas and NumPy to automate workflows and reduce processing time by 20%.

•Optimized complex SQL queries to extract critical business metrics, improving data retrieval efficiency by 15% and enabling faster decision-making.

•Designed and deployed an interactive Tableau dashboard, integrating multiple data sources to enhance insights extraction efficiency by 30% and streamline reporting for stakeholders. Telco Customer Churn Prediction

• Applied advanced machine learning algorithms to predict churn, improving accuracy by 15%.

• Applied feature engineering to identify and transform key predictors, improving model accuracy.

• Implemented model interpretability methods to ensure transparency and foster trust. Cloud-Based ETL Pipeline for Music App Analytics [MongoDB Atlas, Amazon S3, Redshift, Python, Apache Airflow]

• Designed and implemented a scalable ETL pipeline for the music streaming industry, leveraging cloud technologies for data ingestion, transformation, and storage.

• Developed a star schema for data warehousing, enabling efficient querying and analysis of user activity logs and song metadata.

• Engineered advanced data transformation processes, including data cleansing, deduplication, and enrichment, to enhance data quality and readiness for analytics.

• Automated ETL workflows using Apache Airflow, ensuring seamless data integration and real-time insights.

• Validated pipeline performance by executing analytical queries on Redshift, reducing data retrieval time by 30%.

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