About
Highly analytical and results-driven Master of Technology student specializing in Computer Science, with a strong foundation in data engineering and analytics. Proven ability to design and implement end-to-end ETL pipelines, develop robust data models, and create dynamic dashboards using tools like GCP, BigQuery, Power BI, and Python. Eager to leverage advanced data manipulation, visualization, and statistical analysis skills to drive impactful data-driven solutions in a challenging data-centric role.
Projects
Mumbai, Maharashtra, India
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Summary
Developed an end-to-end ETL data pipeline for Uber trip data using GCP tools, enabling efficient analytics and real-time visualization.
Highlights
Developed and deployed an end-to-end ETL data pipeline using Mage on Google Cloud Compute Engine, automating ingestion, transformation, and loading of Uber trip data.
Engineered a star schema data model with Python (Pandas), optimizing data structure for efficient querying and analytics across fact and dimension tables.
Utilized Google Cloud Storage as a robust data staging layer, implementing public access control to facilitate seamless and secure data extraction.
Configured service account authentication and integrated BigQuery Data Exporter within Mage to efficiently load transformed data into the data warehouse.
Constructed a real-time dashboard in Looker Studio, providing dynamic visualization of key Uber trip metrics including distance, passenger count, and payment types.
Mumbai, Maharashtra, India
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Summary
Performed comprehensive sales data analysis for Dominos, transforming raw data into actionable insights and dynamic dashboards using Power BI.
Highlights
Cleaned and transformed a dataset of approximately 49,000 Dominos sales records using Power Query Editor, ensuring data integrity and readiness for analysis.
Calculated critical business metrics including Total Revenue, Average Order Value, and Average Pizza per order by developing custom DAX measures within Power BI.
Designed user-friendly, dynamic dashboards visualizing daily and monthly order trends and analyzing pizza sales percentages by category and size, enhancing business understanding.
Identified and ranked the top 5 and bottom 5 performing pizzas based on Revenue, Quantity, and Total Order, providing insights for menu optimization.
Mumbai, Maharashtra, India
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Summary
Conducted in-depth analysis of over 300,000 road accident records using Excel, delivering actionable insights and visualizations for decision-making.
Highlights
Executed comprehensive data cleaning and transformation on a dataset of over 300,000 road accident records, ensuring data accuracy and readiness for robust analysis and reporting.
Developed a dynamic dashboard in Excel to visualize monthly accident trends and casualty breakdowns, identifying high-risk areas and improving data-driven decision-making.
Utilized multiple pivot tables to aggregate accident data and calculate metrics such as monthly changes in accident rates and casualties by road type, demonstrating strong statistical analysis skills.
Computed key metrics including fatal, serious, and slight casualties, and their respective percentages, providing critical insights to aid strategic decision-making.
Skills
Programming Languages
Python, SQL.
Data Analysis & Engineering
Data Analytics, Data Visualization, Data Wrangling, Exploratory Data Analysis (EDA), Statistical Analysis, ETL, Data Modeling, DAX.
Visualization Tools
Excel, Power BI, Looker Studio.
Databases & Warehousing
MySQL, MongoDB, Snowflake, BigQuery.
Cloud Platforms
AWS, GCP, Google Cloud Compute Engine.
Orchestration & Version Control
Airflow, Mage, GitHub, Git.
Data Transformation
DBT, Power Query Editor.
Development Tools
VS Code, Jupyter Notebook.
Frameworks & Libraries
Linux, Pandas.