Pearl Rwauya

Pearl Rwauya

Abu Dhabi, United Arab Emirates

Pearl Rwauya

Senior Data Engineer
I am an accomplished Principal Data Engineer and ML Infrastructure Architect with over 5 years of experience designing high-availability, petabyte-scale data systems. Throughout my career, I have specialized in transforming raw, unstructured data into reliable, research-grade assets, with a strong track record of supporting academic and scientific research centers. My expertise includes building robust distributed data platforms, optimizing columnar data lakes, and engineering complex ETL/ELT pipelines designed for deep learning inference and massive parallel processing. My services focus heavily on enabling research and center support, including:
Scientific Data Infrastructure: At the NYU Abu Dhabi Mubadala Arabian Center for Climate and Environmental Sciences, I architected an enterprise-grade data lake to centralize climate sensor data, establishing the foundational infrastructure for high-speed research access and deep learning inference.
Research Analytics & Dashboards: I have extensive experience engineering resilient data access layers and custom interactive dashboards (using Streamlit, Plotly, and Dash) to deliver sub-second, real-time scientific insights to global researchers.
Complex Data Harmonization for Studies: For the University of Idaho Department of Mechanical Engineering, I architected data visualization portals to render complex, high-dimensional biomechanical sensor data for advanced analytical modeling.
Data Integrity & Optimization: I automated the end-to-end data lifecycle to ensure 99.9% data integrity for long-term agricultural studies and optimized database indexing to significantly reduce complex analytical query times for research teams.

I provide strategic technical leadership to bridge the gap between raw telemetry and the deployment of enterprise-grade, highly secure AI data products and predictive analytics platforms. Whether you need event-driven architectures on Google Cloud Platform (GCP) or standardized hybrid cloud environments utilizing AWS and Kubernetes, I deliver tailored solutions to empower your research and data operations.

Working hours

  • Monday:08h00 To 18h00
  • Tuesday:08h00 To 18h00
  • Wednesday:08h00 To 18h00
  • Thursday:08h00 To 18h00
  • Friday:08h00 To 18h00
  • Saturday:Not available
  • Sunday:Not available
  • 🇬🇧 English
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