Developed and enhanced data pipelines using Python and SQL in a major biomedical data platform enabling parallel processing of data and reducing the time required to process daily transaction logs from hours to minutes.
Analyzed user requirements, designed and developed ETL processes to load enterprise data into Azure data factory and SQL query by adding indexes to columns frequently used in JOINs, reducing query execution time from 30 seconds to 2 seconds, which enhances user experience for live data querying on the dashboard.
Authored detailed technical documentation and code samples with data flow diagrams and structured source statement commentary using Tableau dashboards. This has improved team onboarding time by 15%.
Conducted rigorous testing of software designs under specified environments and conditions using Python scripts, ensuring optimal performance and functionality. This led to a 25% reduction in critical bugs post-deployment.
Investigated complex problems related to software and data inconsistencies using SQL queries to pinpoint issues. Recommended effective solutions and implemented corrective actions using Python automation tools to maintain quality and consistency, thereby reducing downtime by 15%.
Data Engineer
Visual BI Solutions
06.2021 - 05.2022
Developed and implemented data transformation processes using dbt, employing macros and model files, leading to a streamlined data transformation process by optimizing delivery management data for an American international retailer and reduced delivery errors by 15% by restructuring and optimizing data processing and transforming workflows using dbt
To store and present transformed data, utilized cloud warehouse Snowflake, improving analytics capabilities and providing actionable insights for the BI and Analytics team and enabled a 20% increase in data accessibility and reduced query time by 10%, enhancing the team's ability to generate real-time reports
Built robust data pipelines and leveraged Microsoft Azure, particularly Azure Data Factory and Databricks, leading to more efficient data processing and analysis for the customer feedback handling project which improved data processing efficiency by 25%
Designed front-end visualization by employing Tableau, creating diverse data representations and developing customized dashboards and visualizations resulting in an 11% increase
Utilized Machine Learning algorithms such as KNN and Naive Bayes to perform sentiment analysis on customer feedback data, contributing to identifying trends and patterns to enhance the understanding of customer sentiments
This has helped in Identifying key trends leading to a 10% increase in customer satisfaction scores.
Education
Master of Science - Data Science And Analytics
Florida Atlantic University (GPA 4.0/4.0)
Boca Raton, FL
12-2023
Master of Science - Integrated Software Engineering
Vellore Institute of Technology
Chennai, India
06-2021
Bachelor of Science - Integrated Software Engineering
Vellore Institute Of Technology
Chennai, India
06-2021
Skills
Data Engineering: ETL (dbt)
Cloud Technologies: Microsoft Azure
Data Visualization: Tableau
Programming: SQL, Python
Data Analysis & Insights
Machine Learning
Data Modeling
Data Warehousing
SQL and Databases
Big data technologies
Proficiency in using systems like Git for source code management
Certification
IBM Data Science Professional Certification
Big Data Analytics
Snowflake Essentials
Timeline
Programmer Analyst
Birlasoft
12.2022 - 10.2023
Data Engineer
Visual BI Solutions
06.2021 - 05.2022
Master of Science - Data Science And Analytics
Florida Atlantic University (GPA 4.0/4.0)
Master of Science - Integrated Software Engineering
Vellore Institute of Technology
Bachelor of Science - Integrated Software Engineering