I work at the intersection of data engineering, business analytics, and biomedical data science. My background combines professional experience in databases, BI, and analytics with academic work in health data science and research on energy-aware serverless computing.

I focus on building reliable data systems, transforming complex datasets into actionable insights, and applying analytical methods to real-world business and scientific problems.

What I do

Data & Analytics Engineering

I design and maintain data workflows, reporting layers, and analytical models using tools such as SQL, Python, BigQuery, Power BI, and cloud-based data platforms.

Business Intelligence

I translate raw data into decision-ready dashboards and KPIs, with experience in marketplace analytics, availability metrics, GMV reporting, and operational performance monitoring.

Biomedical Data Science

My academic background connects data science with healthcare, including EHR data, medical imaging, bioinformatics, and predictive modelling.

Green Computing Research

I am currently exploring energy-aware execution of serverless workflows, focusing on measuring and optimizing energy consumption in cloud and Kubernetes-based environments.

Current focus

I am developing my profile as a data professional specialized in analytics engineering, biomedical data science, and sustainable cloud computing.

My current work and research interests include:

  • Data pipelines and analytics infrastructure
  • SQL, Python, BigQuery, and Power BI
  • Biomedical data science and machine learning
  • Energy profiling of serverless workflows
  • Kubernetes-based experimentation
  • Business-impact analytics and KPI modelling

Cloud Analytics

Building scalable data models and reporting systems for business decision-making.

Biomedical AI

Applying machine learning and statistical methods to health-related datasets.

Green Computing

Measuring and reducing the energy cost of distributed and serverless workloads.

Business Intelligence

Creating clear, reliable dashboards that connect technical data with business outcomes.

Selected Projects

Energy-Aware Serverless Computing

Research and experimentation with Lithops, Kubernetes, and energy profiling to evaluate the power consumption of distributed cloud workloads.

Marketplace Analytics

Analytics and reporting work focused on marketplace KPIs, product availability, GMV, and operational business metrics.

Biomedical Data Science

Academic and research-oriented projects involving healthcare datasets, predictive modelling, and biomedical informatics.

Goal

My goal is to build high-impact data systems and analytical models that are useful, scalable, and efficient — especially in domains where data quality, infrastructure, and interpretation matter.