Experienced Data Engineer with 4 years of experience in architecting and developing robust data infrastructures and pipelines on cloud platforms like AWS & GCP. Proficient across full data engineering stack including pipeline development, ETL processes, database design, and data modeling. Currently seeking opportunities as a data engineer/scientist to take on greater technical leadership and strategic initiatives.
• Acquired and integrated sociodemographic, environmental, and health data from diverse sources using advanced techniques like web scraping and spatial data enrichment.
• Performed complex analytics including descriptive statistics, trend analysis, and data visualization utilizing Python, SQL, Excel, Power BI, and STATA.
• Built dashboards, and presentations to summarize key findings for stakeholders and leadership.
• Provided feedback, guidance and graded over 60+ students as TA for Personal Leadership Development course.
• Led 50+ workshops on Microsoft Office 365 among students and promoting the adoption of Microsoft Office 365.
• Utilized Microsoft forms, MSSQL Server, and Power BI to analyze event participation, driving data-informed decisions resulting in a 2X increase in student adoption of Microsoft technologies.
• Built scalable ETL pipeline processing of 10M+ user records using PySpark and AWS Glue from raw to transformed state.
• Streamlined data validation process in ETL pipeline, thereby reducing the data load failures by 40%.
• Partnered cross-functionally with MLOps team and designed data architecture to integrate Health Analytics Report in the Rocket Money app.
• Led the migration of Oracle SQL scripts to BigQuery, efficiently orchestrating data loading and achieving project completion 15 days ahead of schedule.
• Transformed 15+ financial reports by automating end-to-end data pipelines in SSIS, cutting delivery time from 2 days to 5 minutes, enabling Excel exports, and automating stakeholder notifications.
• Streamlined data validation on GCP cloud storage by developing a Python script for row count analysis, reducing processing time from 1 hour to 5 minutes thereby improving the efficiency of data validation tasks by 70%.
• Generated revenue of more than 1M £ by delivering Cross-sell, Up-sell, & Retention campaigns with Marketing team.
• Automated weekly SQL updates with Python after a critical database error, enhancing accuracy and efficiency by 50%.
• Streamlined data processing by automating SQL and Salesforce integration, cutting task time from 5 days to 30 minutes and boosting campaign efficiency.
• Data Research Assistant at IU School of Medicine
• Teaching Assistant for Personal Leadership Development (L-102) at IU School of Public health
• Professional Development officer in Data Science Club of Indiana University Bloomington
