Sai Merugu
@saimerugu
Senior Data Engineer specializing in cloud-native ETL, analytics, and governance for healthcare and enterprise data.
What I'm looking for
I am a Senior Data Engineer with hands-on experience building cloud-first data platforms across Azure, AWS, and GCP, focused on delivering analytics-ready datasets and governed data solutions.
I have designed and implemented scalable ETL/ELT pipelines using Azure Data Factory, Synapse, Databricks, PySpark, AWS Glue, and Airflow, and built dimensional models and Lakehouses to support BI and advanced analytics.
My work emphasizes data quality, security, and compliance — including HIPAA/PHI controls, RBAC, RLS, and data governance with Microsoft Purview — while automating CI/CD, IaC, and operational workflows for reliable delivery.
I collaborate closely with analysts and BI teams to optimize semantic models, improve performance, and enable trusted reporting, bringing a pragmatic focus on performance optimization, documentation, and maintainability.
Experience
Work history, roles, and key accomplishments
Senior Data Engineer
RELEX Solutions
Mar 2024 - Present (1 year 8 months)
Built and maintained Azure data pipelines and Microsoft Fabric lakehouses, improving data reliability and delivering analytics-ready datasets while enforcing HIPAA/PHI compliance and automating CI/CD.
Designed scalable Azure and PySpark data pipelines and dimensional models for clinical data, implemented data quality frameworks and HIPAA/PHI controls, and optimized Synapse workloads for analytics.
Data Engineer
Exposys Data Lab
Jan 2020 - Aug 2022 (2 years 7 months)
Developed and optimized AWS Glue and PySpark ETL pipelines, built dimensional models on Redshift and Snowflake, and implemented Airflow orchestration and CI/CD practices to support supply chain analytics.
Education
Degrees, certifications, and relevant coursework
Sreenidhi Institute of Science and Technology
Bachelor of Science, Computer Science
Bachelor's degree in Computer Science focusing on foundational computer science principles and software engineering practices.
University of North Texas
Master of Science, Computer and Information Science
2023 - 2025
Grade: 3.7 GPA
Activities and societies: Relevant courses: Machine Learning; Deep Learning; Feature Engineering; Big Data and Data Science; AI for Health and Informatics; Human-Computer Interaction.
Master's in Computer and Information Science with coursework in machine learning, deep learning, feature engineering, big data, AI for health, and human-computer interaction; graduated with a 3.7 GPA.
Availability
Location
Authorized to work in
Job categories
Skills
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