Sai Pradeep Reddy Pemmareddy

About Sai Pradeep Reddy Pemmareddy

I believe data engineering is more than building pipelines—it’s about transforming raw information into reliable, scalable systems that power smarter decisions.With a strong foundation in computer science and a Master’s in Computer Technology from Eastern Illinois University, I’ve spent 5+ years engineering data solutions across healthcare, finance, and cloud-native environments. My work focuses on designing architectures that support high-volume, high-impact analytics.I combine engineering creativity with deep technical rigor to build resilient ecosystems—from real-time streaming to ML-ready data platforms.What I do best: Build & optimize large-scale ETL/ELT pipelines using PySpark, Airflow, ADF, Databricks Architect cloud-native lakehouse platforms with Snowflake, Synapse, Redshift, Delta Lake Deliver real-time streaming systems with Kafka, Flink, Kinesis, Stream Analytics🤖 Build ML-ready pipelines & deployment workflows using Azure ML, MLflow, scikit-learn Engineer secure, distributed platforms on AWS, Azure & GCP Automate infra & CI/CD with Terraform, Docker, GitHub Actions, Azure DevOps🧩 Data modeling, governance, lineage & performance optimizationI’ve built systems handling billions of healthcare records, architected low-latency financial data platforms, and supported ML solutions that enhance clinical outcomes and fraud detection.Outside of work, I explore new cloud tools, experiment with personal data projects, and stay curious about emerging engineering frameworks. Let’s connect if you’re into:• Cloud data engineering• Lakehouse & ETL architecture• Streaming technologies• ML pipelines & real-time analytics• Data engineering in healthcare, finance, or AI-driven systems

Experience

1. Data Engineer

   Tata Consultancy Services

   Sep 2024 — Present

   Designed and built scalable ETL pipelines using PySpark, Airflow, Azure Data Factory, and Databricks to process over 2 billion healthcare records.Architected a data lakehouse using Snowflake, Azure Data Lake Gen2, and Synapse, enabling real-time analytics across 50+ clinical departments.Built real-time streaming systems with Kafka, Flink, and Azure Stream Analytics to process HL7/FHIR data from connected medical devices.Developed predictive ML workflows using Azure ML, TensorFlow, and MLflow, improving risk prediction model accuracy by 15%.Implemented secure, compliant CI/CD pipelines using GitHub Actions, dbt, and Azure DevOps, ensuring HIPAA-aligned deployments.

Education

• Eastern Illinois University

  Master's degree, Computer Technology/Computer Systems Technology