Headline

Immediate Joiner | GCP Google Cloud Data Engineer | BigQuery | Dataflow | PySpark | Python | MySQL | ETL/ELT | CI/CD | Git | Cloud Data Pipelines | Airflow | Snowflake | Pub/sub | CloudSQL |

About

Data Engineer with 1.5+ years of hands-on experience in building and optimizing end-to-end cloud-based data pipelines and ETL/ELT workflows on Google Cloud Platform (GCP). Skilled in transforming large volumes of raw data into structured, analytics-ready datasets that support faster, data-driven decision-making. Experienced in designing and developing scalable batch and streaming data pipelines using BigQuery, Cloud Storage, Cloud SQL, Pub/Sub, Dataflow, Dataproc, PySpark, SQL, Python, and Airflow for efficient data ingestion, transformation, and distributed processing. Strong understanding of Medallion Architecture (Bronze, Silver, Gold layers) to manage raw, cleaned, and curated datasets, improving data quality, accessibility, and analytics performance for reporting and analytics use cases. Open to professional opportunities and collaborations as an Immediate Joiner. Email : akashfand00@gmail.com

Location

Pune District

Work experience

Data Engineer GCP at Ecollabraiz Technologies Private Limited, Sep 2025 - Present · 10 mos, Pune/Pimpri-Chinchwad Area, • Developed scalable ETL/ELT pipelines on Google Cloud Platform (GCP) for healthcare analytics and reporting. • Worked with BigQuery, Dataproc (PySpark), Cloud Composer (Airflow), Dataflow, and Cloud Storage for batch and real-time data processing. • Processed patient records, insurance claims, provider, and clinical datasets from multiple data sources including APIs, databases, and flat files. • Implemented data cleansing, schema validation, deduplication, and incremental loading mechanisms to improve data quality. • Built transformation workflows using PySpark and SQL for analytics-ready healthcare datasets. • Optimized BigQuery performance using partitioning, clustering, and query tuning techniques. • Automated workflow scheduling and monitoring using Cloud Composer (Airflow). • Supported reporting and dashboarding requirements by preparing datasets for Looker and Power BI dashboards. • Worked with JSON, CSV, Avro, and Parquet file formats for structured and semi-structured data processing. • Followed HIPAA-aware secure data handling practices using IAM roles, encryption, and secure cloud storage mechanisms.

Data Engineer at Ecollabraiz Technologies Pvt. Ltd., Jan 2025 - Sep 2025 · 9 mos, Pune/Pimpri-Chinchwad Area, • 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- Clickstream Analyst 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 portioning and clustering, cuƫing full-load processing 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.

Education

Bachelor of Science, Science, Dr. Babasaheb Ambedkar Marathwada University

Master of Business Administration - MBA, Data science, Amity University Online