Naga Sahithya

About Naga Sahithya

Data Engineer with 5+ years of experience building scalable real-time and batch data pipelines using Apache Kafka, Spark, and cloud platforms like AWS and GCP. I specialize in designing distributed data systems, messaging architectures, and ETL/ELT workflows that transform complex data into reliable and actionable insights. In my current role, I work on high-throughput streaming pipelines using Kafka and Databricks, focusing on performance optimization, data modeling, and pipeline reliability. I also have experience integrating enterprise data systems using modern data integration approaches similar to Precisely tools, with an emphasis on data quality and governance. I enjoy solving complex data challenges, improving system performance, and building efficient data platforms that support analytics and business decision-making. I am open to opportunities in Data Engineering and cloud-based data platforms.

Experience

1. Data Engineer

   AT&T

   Jan 2024 — Present · Plano, TX, US

   Designed and implemented real-time streaming pipelines using Apache Kafka and Kafka Connect, enabling scalable ingestion across 50+ distributed systems. • Built robust messaging architectures to support asynchronous data processing and system decoupling. • Developed Spark-based ETL pipelines in Databricks for data transformation, aggregation, and enrichment. • Architected Snowflake data models (star schema & normalized) to optimize query performance and reporting. • Implemented enterprise data integration workflows similar to Precisely tools, including data ingestion, replication, transformation, and data quality validation. • Tuned Kafka producers/consumers and Spark jobs, improving throughput and reducing latency. • Automated metadata tracking and data governance processes ensuring high data quality and compliance. • Deployed monitoring frameworks for pipeline debugging, failure detection, and performance tuning.

Education

• Stevens Institute of Technology

  Master's degree, Computer Science