
Data Engineer
Among his key achievements, Gonzalo has developed a real-time data scraping application using Scala, deployed streaming pipelines on AWS, and built end-to-end data architectures. He also successfully integrated proxy solutions from data sources to production, ensuring seamless and efficient data delivery.
Recognized for his precision and adaptability, Gonzalo consistently delivers tailored, high-quality solutions that align with client needs, demonstrating his expertise in data engineering and infrastructure optimization.
Leads data engineering projects utilizing PySpark and Python within a Kubernetes environment, ensuring scalable and efficient workflows;
Optimizes data visualization and monitoring using Elasticsearch, Kibana, and Grafana, enhancing real-time data insights and performance tracking;
Implements and manages CI/CD workflows with ArgoCD, streamlining deployment processes and improving development efficiency;
Contributes to system migration from Kubernetes (k8s) to k3s, achieving a 40% reduction in runtime and costs by improving system efficiency.

Builds scalable data pipelines using Spark and Scala, and engineers a scraping engine on AWS, resulting in a 30% improvement in data quality and volume;
Manages key AWS services such as EMR, Lambda, ECS, Glue, and ECK for efficient data processing and storage;
Streamlines infrastructure provisioning using Terraform and enhances workflow automation with Airflow for optimal system performance.

Develops and manages AWS cloud infrastructures utilizing Spark and Scala for efficient data processing, integrating NoSQL databases to enhance flexibility;
Oversees key AWS services, including EC2, EMR, Glue, and Lambda, for seamless data streaming, while leveraging Athena for optimized querying, resulting in improved data architecture and storage solutions.

Implements CI/CD processes using Jenkins, ensuring streamlined deployment and integration across projects;
Conducts data analysis using Cloudera tools, improving data insights and system performance;
Utilizes Spark-Scala and Control-M for efficient data processing and workflow management, enhancing overall performance and data integration.

Utilizes Spark-Scala and MapReduce for efficient data processing, ensuring optimal performance and scalability;
Analyzes data with Cloudera, generating actionable insights to drive decision-making;
Improves data integration by leveraging Apache Kafka, NiFi, and Oozie, ensuring seamless data flow and enhanced system connectivity.

Develops Fullstack projects using Scala, Python, Java, JavaScript, CSS, Node, and Django, delivering robust and scalable applications;
Utilizes SQL databases for managing transactional data, ensuring data integrity and reliability;
Implements NoSQL databases to handle unstructured customer interactions, optimizing data storage and retrieval for enhanced user experiences.
Engineering excellence
Gonzalo’s overall performance in a 90-minute live technical assessment ranks in the top 15% of vetted Data Engineers at Proxify.

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