Anusha M.

Senior Data Engineer with over 10 years of experience designing and building scalable data platforms and distributed data pipelines across AWS and Azure environments. I specialize in developing cloud-native data solutions using PySpark, Databricks, and modern Lakehouse architectures to enable advanced analytics and data-driven decision making.My expertise includes building enterprise data lakes, developing high-performance ETL/ELT pipelines, and designing scalable data models for analytics and reporting. I have extensive experience working with technologies such as Databricks, Snowflake, Spark, and cloud data services to deliver reliable, high-performance data platforms.I focus on optimizing large-scale data processing systems through performance tuning, automation, and robust monitoring strategies while ensuring data quality, governance, and security across enterprise environments.In healthcare and regulated industries, I have integrated HL7 and FHIR data into cloud-based analytics platforms by building scalable ETL pipelines and structured data models supporting clinical and claims analytics.Technologies I frequently work with include Python, PySpark, Databricks, Snowflake, Azure Data Factory, AWS Glue, and modern cloud data architectures.