Kenneth

Gathered requirements and documented business processes through client discovery and solution planning discussions, translating business needs into technical solutions and application designs. Developed interactive Databricks dashboards and analytics applications that enabled clients to explore operational metrics and real-time business insights.

Created

Databricks applications, visualizations, and reports using Lakehouse architecture, integrating data pipelines and AI capabilities that allowed clients to view real‑time analytics during demonstrations.

Data Intern - Everforth Apex Systems | Databricks Partner Team - Raleigh, NC

(2026-06 - 2026-08)

• Gathered requirements and documented business processes through client discovery and solution planning discussions, translating business needs into technical solutions and application designs.
• Developed interactive Databricks dashboards and analytics applications that enabled clients to explore operational metrics and real-time business insights.
• Created Databricks applications, visualizations, and reports using Lakehouse architecture, integrating data pipelines and AI capabilities that allowed clients to view real‑time analytics during demonstrations.
• Performed data validation and quality assurance testing to ensure reporting accuracy and consistency across analytics solutions.
• Supported Azure and AWS Databricks application deployments and troubleshooting, collaborating with developers via Git and Agile methodologies, which reduced deployment issues and accelerated release cycles.

Business Intelligence System Intern III - City of Virginia Beach – Department of Information Technology - Virginia Beach, VA

(2025-05 - 2025-08)

• Engineered a real‑time environmental data analytics pipeline with Python and the Breeze Technologies API, ingesting and processing over 1.2 million multivariate time‑series sensor records from multiple Virginia Beach monitoring locations.
• Improved data processing efficiency across several systems by adding structured logging and fault‑tolerant mechanisms by creating Pytest‑based API endpoint tests, which reduced processing errors and increased overall system reliability.
• Conducted data quality and backend validation, identifying discrepancies between source data, datasets, and reporting outputs.
• Created test scenarios to verify ETL transformations, data completeness, accuracy, and consistency across pipeline stages.
• Investigated data anomalies and pipeline failures by tracing records through source, transformation, and reporting layers.

Software Engineering Intern - MAG Aerospace - Fairfax, VA

(2023-06 - 2023-08)

• Supported large-scale imaging and simulation data workflows by collecting, processing, and validating high-fidelity infrared datasets used in virtual reality combat-training systems.
• Operated on multi-system imaging stations, ensuring repeatable data ingestion, synchronized capture, data integrity, and consistency across controlled test environments.

Master of Science - Data Science and Engineering - North Carolina Agricultural and Technical State University (2027)

Bachelor of Science - Computer Science - Old Dominion University (2022-01 - 2024-12)