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Anusha Bhetwal

@anushabhetwal

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Senior Data Engineer specializing in cloud-native, secure, production-grade data platforms.

United States

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What I'm looking for

I seek roles building scalable, secure cloud-native data platforms that enable BI/ML/GenAI, emphasize observability, data quality, and collaborative, compliant delivery.

I am a Senior Data Engineer with 6+ years building secure, cloud-native data platforms across GCP, AWS, and Azure, focused on data architecture, reliability, and intelligence enablement. I have owned end-to-end data systems powering BI, ML, and GenAI use cases in healthcare and financial services, and I emphasize data quality, observability, and collaboration with business, quant, and ML teams.

I have delivered measurable improvements including reduced latency SLAs by 40%, lowered query spend by 35%, and accelerated onboarding and maintainability via modular transformations and infrastructure as code. I mentor engineers, drive technical standards, and implement compliant, production-grade pipelines for real-time and batch use cases.

Experience

Work history, roles, and key accomplishments

Current

Senior Data Engineer

Current

Change Healthcare

Jan 2024 - Present (2 years 2 months)

Built HIPAA-compliant PySpark ETL pipelines on Databricks and Airflow to ingest and transform claims data, improving Medicare/Medicaid latency SLAs by 40% and enabling 25+ secure client dashboards. Led migrations to BigQuery/Snowflake and implemented modular dbt transformations to accelerate payer onboarding and improve data quality.

Pyspark Databricks Apache Airflow DBT Pub Sub Dataflow Snowflake BigQuery ETL

Data Platform Engineer

Cardinal Health

Mar 2020 - Dec 2023 (3 years 9 months)

Engineered Spark-SQL and Databricks pipelines and led migration to GCS+Delta Lake and Snowflake, reducing query spend by 35% and shortening onboarding time by 40% via modular PySpark and Dagster assets. Delivered real-time streaming dashboards and integrated observability and cost monitoring for regulated financial workloads.

Spark Databricks Delta Lake Snowflake BigQuery Dagster Pub Sub Dataflow Terraform

ETL Developer

Bank of America

Oct 2019 - Feb 2020 (4 months)

Migrated large-scale financial ETL from Spark/Hadoop to Azure SQL DW, rebuilt T-SQL/SSIS/Informatica pipelines and optimized queries and stored procedures to cut costs and improve nightly batch SLAs by reducing failure rates 30%. Developed Spark and Python pipelines for data cleansing and SCD handling.