Akash Fand

GCP Data Engineer with 1 year of hands-on experience designing and building real-time and batch ELT pipelines on Google Cloud Platform. Proficient in BigQuery, Dataproc (PySpark), Cloud Composer (Airflow), Pub/Sub, and Cloud Storage.

Implemented Medallion

Architecture (Bronze/Silver/Gold layers) and event-driven streaming pipelines for E-commerce and food delivery domains. Strong SQL and Python skills with proven impact on data quality, latency, and processing efficiency.

Data Engineer Intern at Ecollabraiz Technologies Pvt. Ltd. (2025-04 – Present)

• Built end-to-end ETL/ELT pipelines using PySpark (Dataproc), BigQuery, and Cloud Storage for an E-commerce platform, processing daily order and delivery records.
• Designed and deployed a real-time Clickstream Analytics pipeline using Pub/Sub → Cloud Functions → Cloud Storage → BigQuery, reducing data-to-insight latency by 40–55%
• Implemented Medallion Architecture (Bronze, Silver, Gold layers) to organize raw and processed data, improving data quality and downstream query performance by 35%.
• Developed incremental data processing frameworks using BigQuery partitioning and clustering, cutting full-load processing time by 40% compared to full-scan queries.
• Orchestrated batch ETL workflows using Cloud Composer (Airflow) DAGs across 4-7 pipeline stages, ensuring reliable scheduling, dependency management.

B.Sc. – Dr. Babasaheb Ambedkar Marathwada University (2022 – 2025)