Bitan Sarkar

Background

About Bitan Sarkar

I’m a Data Engineer with 4+ years of experience designing, building, and optimizing data platforms, ETL/ELT pipelines, and lakehouse architectures across Azure and Databricks ecosystems. I specialize in leveraging Python, SQL, and PySpark to create scalable, high-performance data solutions that power analytics and business decisions. At Mastercard, I focus on optimizing large-scale data pipelines, reducing query latency, and improving data reliability for analytics teams. Previously, I built data warehouses and lakehouses using Azure Data Factory, dbt, and PostgreSQL, integrating data modeling, governance, and automation best practices. I’m passionate about data architecture, streaming pipelines, and big data frameworks like Apache Spark, Kafka, and Airflow. Recently, I developed a RAG-based AI agent that integrates knowledge graphs, vector databases (Pinecone, FAISS), and LLMs to deliver contextual insights from financial data. I thrive in solving complex data problems end to end — from design to deployment — and mentoring teams to build robust, future-ready data systems. Always exploring ways to bridge data engineering, machine learning, and GenAI for intelligent, automated decision-making.