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Balaji Grandhi

Data Engineer • Hyderabad, India • b*************@gmail.com • +91*******156 • linkedin.com/••••• • drivetube.ai/•••••

Professional Summary

Data Engineer with 0 years of experience specializing in PySpark, Azure Data Factory, Azure Synapse Analytics, SQL and building ETL/ELT pipelines on Azure. Delivered Medallion Architecture pipelines and analytics-ready datasets improving enterprise data availability and reporting performance for business intelligence teams.

Technical Skills

Programming Language: Python,SQL
Databases: Microsoft SQL Server,MongoDB,Azure Synapse Analytics
Cloud Platforms: Microsoft Azure,Amazon Web Services,Azure Data Lake,Storage Gen2
Version Control & Development Tools: Linux,Git,GitHub
Data Engineering & Processing: PySpark,Azure Databricks,Medallion Architecture
Data Analysis & Visualization: Power BI
Data Integration & ETL: Azure Data Factory

Work Experience

Synchroni Global IT Solutions
Hyderabad, India
Data Engineering Intern
January 2026 – Present
Worked at an IT services company delivering data engineering work to ingest and prepare LMS and CMS datasets for enterprise reporting and analytics.
Tech Stack: Azure Data Factory, PySpark, Databricks, Azure Synapse Analytics, Azure Data Lake Storage Gen2, Power BI, Git, GitHub, SQL Server
  • Engineered end-to-end ETL/ELT pipelines using Azure Data Factory, PySpark, and Azure Synapse Analytics to integrate LMS and CMS sources, improving enterprise data availability by 35%.
  • Designed and implemented Medallion Architecture pipelines on ADLS Gen2 with Databricks to standardize ingestion, bronze/silver/gold transformations, and delivery of analytics-ready datasets for reporting teams.
  • Optimized PySpark transformation workflows through Parquet conversion and partitioning strategies, reducing batch processing time and improving pipeline throughput.
  • Implemented Azure Synapse SQL stored procedures, views, CTEs, and window functions to refactor analytical queries and improve query execution and reporting performance by 35%.
  • Collaborated with data engineers and BI developers to design dimensional star-schema models and deliver validated datasets for Power BI, enabling faster self-service reporting for business users.
  • Established version-control and pipeline validation practices using Git and SQL-based data quality checks to improve pipeline reliability and reduce production data incidents.

Projects

LMS Analytics Data Warehouse
Tools Used: Azure Synapse Analytics, Azure SQL, Python, ETL Pipelines, Power BI
  • Architected an LMS Analytics Data Warehouse using Azure SQL, Azure Synapse Analytics, Python, ETL pipelines and Power BI to centralize learner activity and enrollment data, reducing reporting latency.
  • Developed end-to-end ETL pipelines to ingest, cleanse, transform, and load learner activity and enrollment data from multiple source systems into a centralized warehouse.
  • Designed star-schema data models with fact and dimension tables and optimized aggregations, indexing, and SQL queries to improve analytical performance by 45%.
  • Delivered interactive Power BI dashboards to analyze learner engagement, course completion, and instructor performance, enabling faster business intelligence and data-driven decisions.

Education

Swarnandhra Institute of Engineering & Technology
Bachelor of Technology in Artificial Intelligence and Machine Learning • India • June 2020 – August 2024

Certifications

Microsoft Certified: Azure Fundamentals — Microsoft
Microsoft Certified: Azure Data Engineer Associate — Microsoft
AWS Cloud Fundamentals — Amazon Web Services
Python Data Structures — Coursera

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