Ander Martinez-Doñate

I help companies transform complex data into reliable, scalable systems and actionable insights. As a Data Engineer and Data Scientist with a PhD and strong scientific background, I bring a rigorous, analytical approach to designing data solutions that deliver real business value.

I specialize in building end-to-end data platforms using Python, SQL, and Google Cloud (BigQuery, Airflow), focusing on performance, scalability, and automation. My work enables organizations to collect, process, and leverage data efficiently for analytics, reporting, and machine learning applications.

My services include:

• Design and development of ETL/ELT data pipelines

• Cloud data architecture and implementation (Google Cloud Platform)

• Data processing and transformation at scale

• SQL optimization and data modeling

• Workflow automation and pipeline monitoring

• Machine learning integration and predictive analytics

• Data quality improvement and performance optimization

I have experience working with large datasets, building production-ready systems, and solving complex data challenges across scientific and business environments. My background in research and advanced analytics allows me to approach problems with precision, structure, and strong attention to detail.

What differentiates me is a combination of scientific rigor, engineering best practices, and business-focused thinking. I do not just build data solutions — I design systems that are reliable, maintainable, and aligned with measurable outcomes.

My goal is to help organizations unlock the full value of their data by delivering robust infrastructure, efficient workflows, and scalable machine learning solutions that support better decision-making and long-term growth.