I'm a passionate Data Engineer with extensive experience in developing and optimizing data workflows and pipelines. With a background in computer science, I specialize in creating efficient data solutions that drive impactful results.

• Cost Savings: Developed a custom Python-based DAG orchestration framework, resulting in $200k annual savings.
• Efficiency in CI/CD: Established a comprehensive CI/CD pipeline for Snowflake in Azure DevOps, ensuring robust SQL syntax and metadata validation.
• Manual Effort Reduction: Created an XML parser in Azure DataBricks (PySpark), significantly reducing manual effort for schema inference and data flattening.
• Performance Improvement: Optimized the existing ELT framework for Snowflake, cutting data load time by 70%.
• Processing Speed: Built a Python library that decreased the parsing time of 2300 files to around 180 seconds using multiprocessing.

• Programming Languages: Python, Snowflake SQL, Bash Scripting
• Tools & Technologies: Azure DevOps, DASK, Control-M, Pandas, PySpark, SnowPark
• Data Engineering: ETL, ELT, DataBricks, CI/CD, XML Parsing

B.Tech. in Computer Science
Institute of Engineering & Management, Kolkata
Jul 2016 – Jul 2020 | GPA: 7.97/10

Data Engineer (Senior Analyst)
EY | Kolkata, India
July 2022 – Current

• Developed a Python-based custom DAG orchestration framework with runtime restructuring, saving $200k annually.
• Established a comprehensive CI/CD pipeline for Snowflake in Azure DevOps.
• Developed an XML parser in Azure DataBricks (PySpark) to reduce manual schema inference effort.
• Optimized ELT framework for parallel and deadlock-free data load in Snowflake, reducing load time by 70%.
• Created a Python library to efficiently parse 2300 files, reducing parsing time to around 180 seconds.

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I'm always open to discussing new projects, ideas, or opportunities to work together. Feel free to reach out!