APURVA VAZE +1-510-***-**** ad2eaa@r.postjobfree.com

Newark, CA, 94560 GitHub Link: https://github.com/apurvavaze22 LinkedIn: https://www.linkedin.com/in/apurva-vaze

SUMMARY

Experienced Data Analyst with over 8 years in data warehousing and business intelligence, adept at ETL development, data modeling, and performance tuning. Proven track record of delivering impactful and data-driven solutions through collaborative teamwork. Seeking a dynamic Data Analyst role to apply analytical prowess and contribute to data-centric initiatives.

EDUCATION

MS, Business Analytics, Cal State University East Bay, Hayward, USA Jan 2022 – Dec 2023

(Coursework: DBMS, Big Data Tech. & Apps, Data Analytics, Data Warehousing & Business Intelligence, Data Optimization for Analytics, Data Mining, Text Mining, Time Series Analytics, Project Management) BE, Electronics and Tele-communication Engineering, Shivaji University, India Aug 2008 – May 2012 SKILLS

Database Management: Oracle 9i/10g/11g, MySQL Server, Hive, Amazon Redshift, Google Big Query Programming Languages: SQL, PL/SQL, Unix Scripting, Python (pandas, NumPy, matplotlib, scikit-learn, Seaborn, ggplot), R, Natural Language Processing (NLP), Machine Learning (ML) Data Analysis Activities: Data Modeling, Database Performance Tuning, Data Profiling, Data Analysis, Data Optimization, Web scraping

Tools and platforms: Informatica PowerCenter/Data Quality/Big Data Management, Tableau, Talend, Jupyter notebook, WinSCP, AWS, Hadoop, Spark, Excel, Jira

Methodologies: Agile (Scrum), Waterfall

PROFESSIONAL EXPERIENCE

Data Analyst & ETL Developer (Tata Consultancy Services (TCS)) Mar 2013 – Apr 2021

• Analyzed data from several sources, emphasizing expertise in ETL data pipeline solutions and prioritizing data visualization and dashboards for efficient problem-solving.

• Applied advanced analytical skills and quantitative analytics methodologies, including modeling and forecasting, to support strategic decision-making for business performance and efficiency. Developed and sustained comprehensive reporting, dashboards, and visualizations, effectively communicating findings and recommendations to senior management and stakeholders.

• Maintained a vigilant competitive intelligence radar, leveraging extensive experience in handling diverse datasets, SQL/PLSQL query writing, Unix Shell scripting, and Oracle RDBMS databases.

• Positioned as a well-rounded professional through ongoing AWS certification preparation, combining skills to drive data-driven insights and strategies for informed decision-making. PROJECTS at TCS

Data Migration and Enhancement (Client: Reserve Bank of India Role: ETL Lead) Jan 2019 – Apr 2021

• Orchestrated the successful migration of an existing Oracle database to a cloud environment, ensuring efficient and accurate data integration using Agile methodology.

• Established a robust development framework using the Informatica BDM tool, fostering a collaborative environment withing development team.

• Developed an automated testing framework using Oracle stored procedure, reducing manual errors and issues, resulting in a remarkable 30% improvement in data reconciliation efficiency.

• Collaborated with cross-functional teams in daily stand-up meetings to discuss progress and challenges, ensuring timely and transparent communication.

• Worked with the Product Owner to prioritize backlog items and adapt to changing requirements throughout the project. Utilized JIRA to manage and track user stories, tasks, and sprint progress.

• Collaborated closely with business stakeholders to identify key changes and enhancements, leading to improve data model and Informatica mappings, thus enhancing the system performance and efficiency.

• Mentored and guided junior ETL developers, provided technical guidance, and shared industry best practices. Data Cleansing, Enrichment and Upgrade (Client: British Petroleum Role: Sr ETL Developer) Mar 2013 – Dec 2018

• Employed a hybrid approach, integrating Agile principles within a Waterfall framework for the enhancement project. This hybrid approach facilitated flexibility in addressing changing requirements while maintaining a structured project framework.

• Developed and executed changes in the data model, Informatica workflows, and mappings to accommodate the new data feed and also ensured seamless integration of the new source while maintaining existing functionality.

• Worked in close partnership with business users to gain a deep understanding of the changes and enhancements required. Translated business needs into technical solutions for efficient implementation.

• Upgraded Informatica PowerCenter from version 8.1 to 9.5.1 and Kalido DIW/MDM tool from version 8.1 to 8.4, meticulously testing for a smooth transition.

Time Series Forecasting (Scope: Monthly sales forecasting of manufacturing company) Mar 2023 – May 2023

• Extracted monthly sales data for a manufacturing company from Kaggle(Jan 2010 - Dec 2022 and applied various statistical methods of forecasting (Regression based models, two-level Models (Regression + Trailing Average for Residuals, Holt’s Winter method, Auto Arima Model, Auto Regressive models) to predict sales for 2023, aiming to enhance prediction accuracy.

Skills: Time Series Analysis, R (Programming Language) Text Mining (Scope: Sentiment data analysis using NLP techniques) Jan 2023 – May 2023

• Extracted the YouTube comments data set from Kaggle and performed data cleaning activity. Utilized advanced data analysis techniques to perform sentiment analysis, generated word cloud visualizations, analyzed trending tags and views on YouTube, and conducted emoji analysis. Skills: Text Mining, Natural Language Processing (NLP), Sentiment Analysis, python for data analytics Data Mining (Scope: Supervised Learning methods to predict the quality of red wine) Mar 2023 – May 2023

• Explored the dataset of red wine samples from Kaggle and performed data cleaning and preprocessing by removing duplicates and converting the numeric quality column to categorical labels (low, medium, and high)

• Partitioned the data into training and testing sets and trained several supervised learning algorithms, such as classification tree, ordinal logistic regression, and neural networks to predict the quality of red wine.

• Evaluated the performance of each model on the testing data using confusion matrices. After analyzing the results, the main finding was that the classification tree algorithm performed better than the other algorithms in terms of accuracy.

Skills: Data Mining, Machine Learning, python for data analytics Data Analytics : Bay area real estate market analysis with web scraping Aug 2022 – Oct 2022

• Utilized web scraping techniques to collect data from Redfin.com website for 50 properties, providing valuable insights for business decision-making.

• Developed Python scripts to clean the collected data by removing duplicate values, null values, outliers, and other inaccuracies.

• Conducted data analysis to generate residual graphs and prediction calculations, developing both a linear regression model and a Random Forest regression model to discern the factors contributing to price fluctuations in the region.

Skills: Data Cleaning, Data Analysis, python for data analytics DBMS: Netflix Media Database Management System design Mar 2022 – May 2022

• Designed and implemented a database system for Netflix to collect user details and analyze viewing trends, improving the overall user experience, and enhancing the company's market competitiveness.

• Created ER diagram and Relational data model diagram to visually represent the database model.

• Created the prototype database with test data. Based on the required data to be extracted, table JOIN, VIEWS, STORED PROCEDURES were created and executed.

Skills: Database Management System (DBMS), PLSQL, SQL

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