• Passionate about designing, building, and scaling data processing systems.

• I am much more into understanding fundamentals and trying to tackle complex challenges and finding if something valuable I can turn into from raw data

• 📫 How to reach me? sutarhrishikesh00@gmail.com

• Languages: Python, PySpark, SQL
• Big Data Tools: Hadoop, Spark, HDFS, Hive, HBase
• ETL Tools: Informatica PowerCenter, Azure Data Factory, SSIS
• Cloud: Azure (Data Factory, Databricks, Synapse, DevOps)
• Data Engineering: Data Warehousing, Data Modeling, CI/CD, API Integration

• Currently working on project end-to-end ETL pipeline for the insurance domain as of (25th Jan, 2025), including schema modeling.
• Building and optimizing data pipelines with Azure Data Factory and Databricks for large-scale data ingestion.
• Implementing Medallion Architecture and creating curated business views in SQL for data modeling.

• Deepening my knowledge of PySpark for handling large-scale data applications.
• Expanding CI/CD and DevOps skills for seamless data pipeline deployments.
• Learning best practices in cloud data engineering focusing on Azure services.
• 🌱 I’m currently learning and expanding my knowledge in Docker, PySpark, Python DSA, and Kafka
• 🎸 Aspiring Rockstar in the Making! Currently learning guitar, so if you hear any out-of-tune noises, it's all part of the "creative process"! 🎶

1. Master complex data engineering concepts and tools.
2. Specialize in designing scalable data pipelines with PySpark.
3. Contribute to impactful data projects and evolve as a well-rounded data engineer.

• LinkedIn: https://www.linkedin.com/in/hrishikesh-sutar-61490a171/

Let's collaborate and grow in the world of data engineering!