Bikash Thapa Magar

Senior Data Engineer @Publicis Groupe

Developed and enhanced scalable ETL workflows using Apache Spark and Airflow to process multi-format data sources such as JSON, XML, Parquet, and delimited files, supporting finance and risk data pipelines.• Designed and supported real-time ingestion pipelines using Azure Service Bus to ingest financial transactions and regulatory data, enabling responsive trading and compliance platforms.• Led a cross-functional team of data engineers and analysts to deliver a compliant, enterprise-grade data lake platform that consolidated clinical, operational, and financial datasets across business units.• Mentored junior engineers on Spark performance tuning, PySpark best practices, and secure data pipeline design aligned with HIPAA compliance standards.• Tuned Spark job performance and optimized cluster configurations to handle petabyte-scale data volumes, improving financial query response efficiency for data science and reporting teams by over 40%.• Integrated portfolio, accounting, and investment datasets from client-facing systems into unified analytical views to support onboarding of institutional partners.• Built end-to-end pipelines on Google Cloud Platform (GCP) using Azure SQL, Cloud Composer (Airflow), DataProc, and Pub/Sub to enable real-time business intelligence on real estate and healthcare asset flows.• Created star-schema based dimensional models to support healthcare and financial operations reporting across internal BI tools.• Implemented pytest-driven validation layers across ETL pipelines to ensure accuracy, consistency, and compliance with internal QA standards.