Pallavi Shrestha

About Pallavi Shrestha

As a Data Engineer at Fusemachines, my role is to convert intricate datasets into actionable insights, and I\'ve excelled in designing scalable ETL pipelines and data quality frameworks. We\'ve automated processes using AWS architectures and developed business intelligence dashboards that enhanced reporting efficiency and accessibility, significantly improving workflow performance. Holding a Master\'s degree in IT with a focus on Data Science, I leverage my education and hands-on experience in data engineering & analytics to empower our organization\'s decision-making. Our team has optimized data systems, reducing feature preparation time for fraud detection, and we\'ve bolstered data reliability by resolving critical discrepancies, all contributing to a culture of data-driven excellence.

Experience

1. Data Engineer Analyst

   Fusemachines

   Feb 2022 — Present · NY, US

   Fusemachines is a leading AI company delivering transformative IT, AI, and data solutions to clients worldwide. As a data engineer, I designed scalable ETL pipelines, automated workflows, and developed BI dashboards, enhancing data quality and accessibility across projects- Fuse Data Automation and Analytics Platform: Automated data workflows using AWS Medallion Architecture. Built PySpark and SparkSQL scripts in AWS Glue for cleaning and transforming data, optimizing performance by 40%. Designed dashboards in Apache Superset, improving reporting efficiency by 35%- Fraud Detection AI Engine: Designed SQL-based pipelines in AWS Redshift, generating 98 features from hundreds of tables, reducing feature preparation time by 35%. Automated workflows with Airflow, enabling real-time fraud detection with thousands of rows processed every 15 minutes. Built dashboards in Looker to analyze fraud patterns, reducing investigation time by 20%- OTG Enterprise Data Warehouse: Ensured data reliability with quality checks in AWS Redshift and PostgreSQL, improving reliability by 25%. Enhanced ETL pipelines with Python scripts and AWS Lambda, improving workflow efficiency by 20%- Fuse Data Quality Framework: Developed Spark-based transformations in AWS Glue and a Superset-based Data Quality Dashboard integrated with Athena, enabling real-time monitoring and validation across projects.Instructor & Mentor Trained 200+ global fellows in SQL, Apache Spark, and data visualization as part of Fusemachines AI Fellowship and Apprenticeship Programs. Designed and delivered sessions, resulting in 80% of trainees securing associate roles.Skills: SQL (MySQL, PostgreSQL, AWS Athena), Python (Pandas, NumPy, SQLAlchemy, BeautifulSoup, etc.), Apache Spark (PySpark, SparkSQL), AWS (S3, Glue, EC2, RDS, EMR, Lambda, IAM, Redshift, MWAA), Apache Airflow, Airbyte, MongoDB, Apache Kafka, Snowflake, Amazon Redshift, Looker, Apache Superset, Git, Github, Bitbucket, Docker, Automation

Education

• Leeds Beckett University

  Master's degree

• Bhu. Pu. Sainik Higher Secondary School

  School

• SOS Hermann Gmeiner School Bharatpur

  High School

• Fusemachines

  Microdegree

• Agriculture and Forestry University

  Bachelor's degree