Lithin Somavarapu
Fort Worth
Summary
Results-driven Data Engineer with 2+ years of experience designing, building, and testing scalable data pipelines in cloud environments. Strong expertise in AWS (S3, Glue, Lambda, Redshift, Athena, EMR), Python automation, SQL optimization, CI/CD, and Kubernetes. Experienced in cloud migration, ETL testing, and building automated data validation frameworks. Focused on delivering high-quality, reliable, and scalable data solutions.
Overview
6
6
years of professional experience
Work History
Data Engineer
Quadrant Technologies
01.2024 - 01.2026
- Designed and maintained scalable AWS-based ETL pipelines using S3, Glue, Lambda, and Redshift.
- Built PySpark transformation jobs to process large datasets (millions of records) with improved performance.
- Developed automated Python-based data validation framework to perform row count, schema, and business rule validation.
- Optimized SQL queries for large datasets, improving query performance by 30%.
- Implemented monitoring using CloudWatch alarms to detect and resolve pipeline failures proactively.
- Collaborated with business analysts and developers to implement complex transformation logic.
- Participated in migration of legacy on-prem ETL workflows to AWS cloud environment.
- Automated deployment pipelines using CI/CD tools and containerized workflows using Docker and Kubernetes.
- Designed and maintained data models for analytics and reporting requirements.
- Ensured data integrity and compliance with enterprise data management policies.
Data Engineer
Integration Developer Network
02.2020 - 08.2021
- Assisted in automation of deployment processes using Jenkins and shell scripts.
- Supported database operations and wrote SQL queries for data validation.
- Monitored application logs and resolved production data issues.
- Collaborated with cross-functional teams to maintain system reliability.
Education
Master of Science - Information Technology
University of Cumberland’s
12.2023
Skills
- Cloud Platforms: AWS (S3, Glue, Lambda, Redshift, Athena, EMR, CloudWatch), Azure
- Programming & Scripting: Python, SQL, PySpark, Scala (basic), Shell Scripting
- Data Engineering: ETL, Data Warehousing, Data Modeling, Data Lakes
- Big Data Tools: Spark, Airflow, Glue
- Databases: Redshift, PostgreSQL, MySQL
- CI/CD & DevOps: Jenkins, GitHub Actions, Terraform, Docker, Kubernetes
- Monitoring & Visualization: CloudWatch, Prometheus, Power BI (basic)
- ETL Tools Exposure: Informatica, Alteryx, AWS Glue
Project Highlights
AWS Cloud Data Platform
- Built end-to-end data pipeline from ingestion (S3) to transformation (Glue) to warehouse (Redshift).
- Implemented partitioning and Parquet format to reduce Athena query costs by 25%.
- Created automated ETL testing scripts using Python.
- Designed monitoring dashboards for pipeline health tracking.
Timeline
Data Engineer
Quadrant Technologies
01.2024 - 01.2026
Data Engineer
Integration Developer Network
02.2020 - 08.2021
Master of Science - Information Technology
University of Cumberland’s