Headline

Data Engineer | SQL | Snowflake | AWS Glue | ETL | Tableau | Healthcare Analytics | Data Consultant

About

Data Engineering professional with 3 years of experience in healthcare analytics, ETL development, and cloud-based data engineering. Experienced in SQL, Snowflake, AWS Glue, Tableau, Python, Hadoop, and Apache Spark. Skilled in data ingestion, transformation, data validation, reconciliation, and troubleshooting across large-scale healthcare datasets. Passionate about solving complex data problems, improving data quality, and delivering reliable analytics solutions. Currently seeking opportunities in Data Engineering, Data Analytics, and Data Consulting.

Location

Secunderābād

AI stack

claude code

gemini

github copilot

ChatGPT

Microsoft Copilot

Work experience

Associate Software Engineer at Carelon Global Solutions India, Jul 2026 - Present · 5 mos, Hyderabad, Telangana, India, National Cost Consumer Transparency (NCCT) Healthcare analytics platform focused on delivering cost transparency data for hospitals and physicians across the United States. Contributed to cloud-based ETL workflows using AWS Glue, Snowflake, SQL, and Tableau by performing data transformation, validation, reconciliation, and reporting to ensure accurate, analytics-ready datasets for business stakeholders.

Data Engineer at Carelon Global Solutions India, Jul 2023 - Present · 3 yrs 5 mos, Developed and optimized AWS Glue ETL jobs using Python (PySpark) to ingest and transform large-scale healthcare datasets, improving pipeline performance through job tuning and parallelization. Contributed to the migration of data processing workflows from on-premise Hadoop to AWS Cloud (S3, Glue, EC2), improving scalability and reducing infrastructure overhead. Built complex SQL queries in Snowflake across 50+ tables using multi-table joins, window functions, CTEs, and aggregations to deliver analytics-ready datasets for downstream BI teams. Engineered data reconciliation frameworks to detect and resolve record count variances across source, staging, and target layers — improving data accuracy across reporting pipelines. Developed and optimized Tableau dashboards with calculated fields, dynamic filters, and parameters; performed end-to-end data validation between transformed datasets and Tableau outputs consumed by 3 business teams. Collaborated cross-functionally with data engineers, analysts, QA, and business stakeholders to translate business rules into technical data logic for healthcare cost transparency reporting.

Education

Bachelor of Engineering, data science and big data analytics, kl university

Bachelor of Technology, kl university