Data Engineer - AWS Cloud-Native Data Platforms Expert

Divya Kola

Chantilly, VA, — ***********@*****.*** — +1-216-***-****

Summary

Data Engineer with 3+ years of experience building and maintaining AWS cloud-native data platforms for large-scale analytics and enterprise reporting. Strong expertise in Python, SQL, PostgreSQL, and Oracle, along with modern data tooling including AWS Glue, dbt, and Databricks. Proven ability to design scalable data pipelines, support database migrations, write well-tested code, and collaborate with cross-functional teams to deliver reliable, production-grade data systems.

Education

Campbellsville University, Kentucky, USA Jan 2023 – Aug 2024 Master of Science in Computer Science — GPA: 4.0 / 4.0 Jawaharlal Nehru Technological University, Hyderabad, India Jun 2017 – Apr 2020 Bachelor of Technology in Computer Science & Engineering — GPA: 3.4 / 4.0 Technical Stack

• Cloud Platform (AWS): S3, EC2, RDS, Glue, Lambda, IAM, CloudWatch

• Data Engineering & Pipelines: ETL/ELT pipelines, batch and near real-time processing, AWS Glue

• Databases: PostgreSQL, Oracle, SQL Server (schema design, indexing, query optimization)

• Programming: Python, SQL, PySpark, Shell Scripting

• Data Integration: Databases, REST APIs, streaming platforms, PDF and MS Office file ingestion

• Data Management & Quality: Data cleaning, validation, versioning, data quality checks

• Data Modeling: Relational modeling, dimensional modeling, analytics-ready datasets

• Monitoring & Reliability: AWS CloudWatch, logging, pipeline monitoring, performance optimization

• DevOps & Collaboration: Git, Linux environments, Agile/Scrum, code reviews, technical documentation Professional Experience

Defend Remote, USA

Data Engineer (AWS) Jun 2025 – Present

• Implemented and enhanced AWS-based data pipelines to support large-scale analytical and reporting datasets.

• Developed Python ETL workflows using AWS Glue and Lambda to ingest, transform, and validate structured data.

• Designed and optimized PostgreSQL and Oracle schemas to ensure high performance and scalability.

• Supported data migration initiatives, consolidating legacy datasets into a harmonized AWS environment.

• Built and maintained data validation checks to improve data reliability and consistency.

• Wrote clean, well-tested code following engineering standards and participated in peer code reviews.

• Contributed to technical documentation, deployment processes, and production support activities. Sutherland Global Services Hyderabad, India

Data Engineer Jan 2020 – Jul 2022

• Built and maintained ETL/ELT pipelines using Python and SQL in AWS environments.

• Designed relational data models and implemented PostgreSQL and Oracle database solutions.

• Assisted with database migration and modernization projects supporting analytics platforms.

• Improved data reliability through validation checks, error handling, and performance tuning.

• Worked closely with stakeholders to translate requirements into scalable technical solutions.

• Followed SDLC best practices and supported testing, documentation, and release activities. Academic Projects

Cloud-Based Research Data Pipeline

Python, AWS Glue, PostgreSQL

• Built a scalable AWS data pipeline to ingest and process high-volume datasets.

• Designed database schemas and implemented validation logic to ensure data integrity. Analytical Data Modeling Project

AWS, SQL, dbt

• Developed relational data models and transformations using dbt.

• Enabled efficient querying and downstream analytics through optimized schema design. Certifications

• NVIDIA: Fundamentals of Machine Learning

• NVIDIA: Fundamentals of Deep Learning

• NVIDIA: Fundamentals of NLP

• SoloLearn – SQL Certification

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