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Kusum Ranabhat

@kusumranabhat

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Senior Data Engineer with expertise in scalable data platforms.

United States

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What I'm looking for

I seek a collaborative environment that fosters innovation and supports career growth.

I am a Senior Data Engineer with over 6 years of experience in building scalable, cloud-native data platforms and modernizing enterprise data infrastructure across various domains, including healthcare, insurance, and finance. My expertise lies in designing real-time and batch data pipelines using AWS, Azure, and GCP, which support analytics, machine learning, and compliance use cases. I have a proven track record of architecting solutions that leverage data lakehouse, data mesh, and medallion architecture principles, ensuring reusability and scalability.

Throughout my career, I have successfully collaborated with data science teams to deliver curated, ML-ready datasets for predictive modeling and risk analysis. I am passionate about data quality and have implemented robust validation, schema evolution, and metadata standardization processes. My hands-on experience with tools such as Apache Spark, PySpark, and SQL, combined with my strong understanding of distributed systems and cloud technologies, enables me to drive impactful data solutions that align with business objectives.

Experience

Work history, roles, and key accomplishments

Current

Senior Data Engineer

Current

CVS Health

Nov 2023 - Present (1 year 9 months)

Designed and maintained cloud-native ETL pipelines using AWS Glue, Lambda, and S3 to support pharmacy benefits data integration, claims processing, and payer analytics across multiple business units. Engineered real-time data ingestion for prescription transactions by integrating Apache Kafka with AWS Lambda and Amazon Kinesis, enabling low-latency processing for operational analytics and fraud de

AWS Glue AWS Lambda Amazon S3 Amazon Redshift AWS Step Functions Amazon EMR Apache Kafka Pyspark Python SQL

Data Engineer

Allstate

Feb 2020 - Present (5 years 6 months)

Designed and deployed robust ETL pipelines using AWS Glue and Lambda to automate ingestion/transformation of policy, claims, and telematics data, accelerating data availability for analytics. Built and maintained a centralized Amazon S3 data lake for structured and semi-structured data, and engineered real-time streaming pipelines using Kinesis and Lambda to ingest telematics and sensor data from

AWS Glue AWS Lambda Amazon S3 AWS Step Functions Amazon Kinesis Apache Airflow Azure Data Factory Google BigQuery Pyspark Python

Data Engineer

Northwestern Mutual

Jun 2017 - Present (8 years 2 months)

Developed scalable ETL pipelines using Azure Data Factory (ADF) to ingest and transform financial, client, and transaction data from various enterprise systems. Architected distributed analytics pipelines in Azure Synapse Analytics, delivering high-performance query layers for actuarial modeling, risk profiling, and regulatory reporting.

Azure Data Factory Azure Functions Azure Synapse T SQL SQL Server Azure DevOps Azure Key Vault Python

Education

Degrees, certifications, and relevant coursework

Midwestern State University

MBA, Business Analytics

Completed an MBA with a specialization in Business Analytics. The program focused on leveraging data for strategic decision-making and business intelligence.