Description

• Designed, developed, and optimized complex data pipelines to ingest, process, and store data from Google Cloud Storage (GCS) to BigQuery.

• Built API-integrated workflows to fetch data from external APIs, process responses, and load results into downstream systems.

• Implemented Pub/Sub–based event-driven pipelines supporting both real-time and batch data processing, including triggers and message handling.

• Created and managed BigQuery DDLs, views, and authorized views, ensuring secure data access through appropriate roles and permissions.

• Improved ETL pipeline and SQL query performance, reducing processing time and enhancing BigQuery warehouse efficiency.

• Conducted DEV and UAT testing, validating business logic, data quality, and end-to-end pipeline stability.

• Applied business transformation logic to convert raw data into analytics-ready datasets.

• Generated weekly and monthly SQL-based reports and automated their distribution via email for business stakeholders.

• Collaborated with client and business stakeholders to gather requirements and deliver accurate, efficient, and interpretable data solutions.

• Developed interactive dashboards using Looker Studio to enable clear data visualization and reporting

Key Skills

Education

Bachelor's degree