Shreyash Chavan

Data Engineer | ETL Developer | Cloud Data Integration Specialist
Pune, IN.

About

Results-driven Data Engineer with a proven track record in designing, building, and optimizing scalable cloud-based ETL pipelines, adept at leveraging Python, PySpark, and the Azure Data Platform (ADF, Databricks, SQL, Power BI). Expert in data modeling, integration, transformation, and real-time analytics, I consistently deliver solutions that automate data ingestion, orchestrate complex workflows, and drive actionable insights. Eager to contribute expertise as a Data Engineer, ETL Developer, or Cloud Data Integration Specialist to advance enterprise data capabilities.

Work

Digital Zone
|

Data Engineering Associate

Pune, Maharashtra, India

Summary

As a Data Engineering Associate at Digital Zone, I designed, automated, and deployed scalable ETL pipelines and data workflows, significantly enhancing data processing efficiency and analytical insight delivery.

Highlights

Engineered and automated scalable ETL pipelines utilizing Python and SQL, significantly reducing manual data processing efforts by 25%.

Implemented CI/CD methodologies within Azure Data Factory (ADF) to streamline ETL pipeline deployments, ensuring seamless updates and error-free workflows across diverse environments.

Developed and deployed robust data pipelines that transformed raw data into analytics-ready datasets, directly enabling 50+ actionable insights for strategic decision-making.

Automated and centralized data ingestion from various sources, including APIs, flat files, and relational databases, leveraging Azure Data Factory for efficient storage.

Collaborated cross-functionally to deploy end-to-end data workflows using ADF and Azure Databricks, facilitating enterprise-scale data integration and accessibility.

Itelligence Infotech Private Ltd
|

Data Science Intern

Pune, Maharashtra, India

Summary

As a Data Science Intern at Itelligence Infotech, I designed and implemented ETL pipelines and analytical solutions, significantly improving data integration efficiency and delivering critical business insights.

Highlights

Designed and implemented robust ETL pipelines in Azure Data Factory, streamlining data ingestion from multiple sources and reducing manual integration efforts by 50%.

Integrated Azure SQL Database with Power BI to develop and deliver real-time, interactive dashboards, providing critical insights for leadership teams.

Utilized Azure Data Factory and Azure Data Lake to deliver complex analytical tasks on time, enabling 40% faster data processing and scalable analytics through exceptional problem-solving.

Education

University of Pune
Pune, Maharashtra, India

Bachelor of Engineering

Mechanical Engineering

Grade: CGPA: 8.19

Skills

Programming & Scripting

Python, PySpark, T-SQL.

Cloud & Big Data Tools

Azure Data Factory, Azure Databricks, Azure Data Lake.

Data Integration & ETL

ADF Pipelines, Stored Procedures, Data Transformation.

Databases

SQL Server, MySQL.

Data Modeling

Star Schema, Snowflake Schema, Data Warehousing.

Version Control & Dev Tools

GitHub, VS Code, Jupyter Notebook.

Projects

Azure Data Engineering Pipeline

Summary

Designed and implemented a comprehensive Azure-based data engineering pipeline, leveraging Azure Data Factory, Azure Blob Storage, Azure SQL Database, and Power BI to demonstrate end-to-end data workflow capabilities.

Healthcare Claims Data Pipeline

Summary

Developed and deployed a robust healthcare claims data pipeline using Azure Data Factory, Azure SQL Database, Azure Databricks (PySpark), and Power BI to process, integrate, and analyze complex medical data.