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Inisha Khadka

@inishakhadka

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Experienced data engineer specializing in cloud-based data architectures.

United States

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What I'm looking for

I seek a challenging role in a dynamic environment that fosters innovation and professional growth.

With over seven years of experience in designing, implementing, and managing cloud-based data architectures, I have developed a strong expertise in building scalable data pipelines and optimizing data ingestion workflows. My proficiency in technologies such as Apache Spark, Snowflake, and AWS has enabled me to deliver high-performance solutions that drive business insights and analytics.

Currently, as a Senior Data Engineer at Johnson & Johnson, I have successfully designed and optimized ETL pipelines, significantly reducing processing latency and improving event throughput. My role involves collaborating with cross-functional teams to develop real-time data sharing solutions and implementing cloud automation strategies that enhance operational efficiency. I am passionate about leveraging my skills in data governance and visualization to create impactful dashboards that support data-driven decision-making.

Experience

Work history, roles, and key accomplishments

Senior Data Engineer

Johnson & Johnson

Jun 2022 - Present (3 years 2 months)

Designed and optimized ETL pipelines using PySpark, processing large-scale healthcare datasets from Medicare, Medicaid, and commercial lines to support advanced analytics. Built a real-time ingestion pipeline using Spark Streaming, Apache Flink, Kafka, and AWS Kinesis, reducing processing latency by 50% and increasing event throughput.

Data Engineer

Bank of America

Sep 2019 - Present (5 years 11 months)

Designed and implemented advanced data pipelines using Azure Data Factory and Apache Airflow, automating ETL workflows for seamless scheduling, monitoring, and execution across diverse environments. Built scalable data engineering solutions leveraging Azure Synapse Analytics, Azure Data Lake Storage (ADLS), and Databricks, supporting both real-time and batch processing requirements.

ETL Developer

The Kraft Heinz Company

Feb 2018 - Present (7 years 6 months)

Designed and implemented robust ETL pipelines using Informatica PowerCenter, ensuring data integrity, quality, and efficient integration from SQL Server, Oracle. Built high-performance data processing applications using Spark (PySpark, Spark-SQL), significantly improving data transformation speed and pipeline efficiency.