Daniel Alonso Pujol is a dedicated Cloud Engineer at Keepler Data Tech, where he leverages his expertise in cloud computing and data engineering to drive innovative solutions for complex data challenges. With a strong foundation in both Google Cloud Platform (GCP) and Amazon Web Services...
Daniel Alonso Pujol is a dedicated Cloud Engineer at Keepler Data Tech, where he leverages his expertise in cloud computing and data engineering to drive innovative solutions for complex data challenges. With a strong foundation in both Google Cloud Platform (GCP) and Amazon Web Services (AWS), Daniel specializes in utilizing a diverse array of tools and services, including Cloud Functions, BigQuery, and AWS Glue, to architect scalable data pipelines and enhance data accessibility. His proficiency in Python and SQL enables him to develop robust data processing scripts and perform intricate data analysis, ensuring that insights are readily available for decision-making.
At Keepler, Daniel is actively involved in key projects that focus on optimizing cloud infrastructure and implementing data solutions that empower businesses to harness the full potential of their data. His experience with Big Data technologies, such as PySpark and Apache Airflow, allows him to manage large datasets efficiently and automate workflows, significantly improving operational efficiency. Additionally, his knowledge of dbt and Apache Druid positions him as a valuable asset in transforming raw data into actionable insights.
Daniel's commitment to continuous learning and collaboration is evident in his desire to work alongside a top-tier team, where he can both share his knowledge and absorb new skills. His interests in machine learning further complement his role, as he seeks to integrate advanced analytics into cloud solutions, driving innovation and enhancing business outcomes. With a keen eye for detail and a passion for technology, Daniel Alonso Pujol is poised to make significant contributions to the evolving landscape of cloud data engineering.
