Kundeti Lakshmi Sai

Leawood,KS

Summary

Results-driven Cloud Computing Engineer with over 4 years of hands-on experience in leveraging AWS technologies, including Glue, EMR, Redshift, S3, Airflow, Spark, Hudi, Iceberg, and Terraform. Expertise in modernizing data platforms to enhance performance and automating infrastructure through CI/CD and Infrastructure as Code practices. Strong background in designing, deploying, and managing cloud infrastructure with an emphasis on automation, scalability, and security. Recognized for fostering collaborative team environments and adapting to evolving project needs while delivering reliable and strategic solutions.

Overview

years of professional experience

Certification

Work History

Cloud Engineer

USAA

San Antonio, TX

03.2025 - Current

Designed and implemented scalable data platforms on AWS using Glue, S3, Lambda, and Redshift, improving pipeline reliability and performance.
Built and optimized end-to-end batch and near real-time data pipelines processing large-scale datasets from multiple source systems.
Developed PySpark-based ETL frameworks on AWS Glue and EMR for distributed data processing and complex transformations.
Implemented robust data quality checks (validation, reconciliation, cleansing) using Python and SQL within Glue workflows.
Designed and optimized Athena queries for ad-hoc analytics on S3, improving query performance and reducing cost through partitioning and optimization.
Orchestrated workflows using Apache Airflow, building modular DAGs, managing dependencies, and improving monitoring and alerting.
Migrated legacy/on-prem workloads to AWS, enhancing scalability and reducing infrastructure overhead.
Built reusable Terraform modules for provisioning AWS infrastructure (Glue jobs, EMR clusters, S3, IAM), enabling consistent environments.
Integrated Terraform with CI/CD pipelines to automate infrastructure changes and application deployments.
Implemented Apache Hudi (COW/MOR) to support incremental data processing, versioning, and efficient upserts in the data lake.
Implemented Apache Iceberg integrated with Spark and Glue for ACID compliance, schema evolution, and time travel capabilities.
Strengthened security posture using IAM, Lake Formation permissions, and governance best practices.
Used CloudWatch for logging, monitoring, and alerting across pipelines and infrastructure.
Mentored junior engineers, conducted code reviews, and contributed to best practices documentation.

Data Engineer

HCL

Hyderabad, India

10.2022 - 11.2023

Developed AWS-based data pipelines using Glue, S3, and Airflow to support analytics and reporting use cases.
Built and maintained Airflow DAGs for scheduling and monitoring ETL workflows.
Implemented security best practices using AWS IAM and KMS for encryption and access control.
Automated ETL processes using AWS Lambda to reduce manual operational effort.
Designed and optimized SQL workloads for improved query performance.
Implemented CI/CD pipelines using AWS CodePipeline and GitHub Actions.
Used CloudWatch for monitoring, alerting, and operational visibility.
Participated in Agile delivery, contributing to sprint planning, reviews, and retrospectives.

Jr. Data Engineer

SoftSol

Hyderabad, India

10.2020 - 09.2022

Supported development of AWS-based data pipelines and ETL workflows for enterprise clients.
Assisted in building data workflows using Databricks and cloud data integration tools.
Supported database administration tasks including backup, recovery, and performance tuning.
Contributed to documentation, testing, and deployment support for data solutions.
Collaborated with senior engineers on architecture design and best practices.
Actively upskilled on AWS services and data engineering fundamentals.

Education

Masters - Computer Science

University of Central Missouri

Missouri City, MO

01-2025

Skills

Cloud & Platforms: AWS (Glue, S3, Redshift, Lambda, EMR, Athena, Lake Formation, IAM, CloudWatch)
Data Engineering: PySpark, Python, SQL, ETL/ELT, Data Modeling, Data Quality, Data Governance
Orchestration & Workflow: Apache Airflow, AWS Step Functions
Data Lake Technologies: Apache Hudi, Apache Iceberg

Data Warehousing: Amazon Redshift, Snowflake
Big Data: Spark, Hadoop
IaC & DevOps: Terraform, Jenkins, AWS CodePipeline, Git
Databases: AWS RDS, DynamoDB