Building Systems That Power Better Decisions
The Department of Information Systems is proud to spotlight Akanksha Patel, M.S. ’26, information systems, a recent graduate of the Information Systems program. During her time at UMBC, Akanksha served as a graduate student worker at the Department of Information Systems front desk, where she supported faculty, staff, and students with daily administrative operations while contributing to a welcoming and efficient department environment. Alongside her campus involvement, she built an impressive portfolio of work in data engineering, cloud infrastructure, analytics, and machine learning, demonstrating the technical expertise and collaborative spirit that define our IS community.
Akanksha is a data engineer with a background in building scalable pipelines, cloud infrastructure, and analytics systems that drive measurable impact. Prior to UMBC, she previously spent two years at Cognizant Technology Solutions in Pune, working across large-scale data engineering and ETL initiatives.
Her core technical stack includes Python, SQL, dbt, Snowflake, and AWS, with additional experience across Azure and GCP. She has also worked extensively with Spark, Kafka, Airflow, and Terraform in production environments. Akanksha is passionate about clean architecture, reproducible workflows, and building reliable data systems that stakeholders can trust.
Her project experience during graduate school, spans multiple areas of data engineering and analytics. She developed a lending analytics pipeline using dbt and Snowflake, with a strong emphasis on clean, well-tested data models that supported reliable business analysis. She also designed a real-time streaming pipeline using Kafka and PySpark to support scalable machine learning inference beyond notebook-based workflows.
In the healthcare domain, she built an analytics reporting system where data governance and auditability were foundational components rather than afterthoughts. One of her most comprehensive projects involved designing an end-to-end sensor data pipeline integrating Kafka, Spark Streaming, MongoDB, PostgreSQL, FastAPI, Streamlit, and Airflow into a cohesive architecture that she managed from development through deployment.
Her capstone project focused on a Multi-Cloud Architecture Recommender designed to help organizations identify the most suitable AWS, Azure, or GCP infrastructure based on workload requirements. She also developed a malicious URL detection model using Random Forest, Isolation Forest, and PCA, achieving a ROC-AUC score of 0.92 while prioritizing both performance and model explainability.
Beyond the technical aspects of engineering, Akanksha is especially interested in solving problems at the intersection of data and real-world impact, including healthcare analytics, fintech pipelines, and systems that enable organizations to make faster, more informed decisions.
She is currently open to full-time opportunities in data engineering, analytics engineering, and business intelligence roles across the United States.
To learn more about Akanksha and her work, connect with her on LinkedIn.
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