Architected and developed RESTful API and database schema (tables, views, indexes) for an application that aggregates real estate transaction data.

Designed and built data ingestion processes using Python and SQL to validate, transform, and load 1M+ real estate transaction records.

Developed and automated ETL pipelines using Airflow and Python to ingest and standardize 15+ third-party sources, delivering consistent and reliable data for downstream applications.

Implemented event-driven CDC pipelines leveraging Debezium, Apache Kafka (AWS MSK), AWS Lambda, and Python to capture real-time database changes and trigger metric calculations, updates, and audits.

Delivered analytics-ready datasets and Power BI dashboards providing insights into property performance, pricing, and investment KPIs.

Partnered with cross-functional teams to resolve production issues and ensure data reliability.

Created test suite using Python and Selenium to automate feature testing.

Developed website features using HTML, CSS, JavaScript, and Bootstrap.

Utilized Python and Selenium to gather restaurant website data for pricing and industry trend analysis.

Developed Java and SQL scripts to track database changes and generate reports.

Collaborated with clients to troubleshoot and resolve system errors.

Developed Python scripts that generate release reports containing robot diagnostics, bug tracking, and software revision information.

Automated bug-fix verification using Python scripts that analyze system logs and update bug reports.