Design, implement, and operate end-to-end MLOps capabilities, leading centralized feature management and automated pipelines that guarantee consistency between training and serving, quality control, versioning, and reproducibility. Work cross-functionally with multidisciplinary teams to bring models to production securely, scalably, and reliably, with a current focus on pricing business cases.

Defined the Lakehouse architecture in Azure incorporating governance and cost control; led modernization and automation under agile frameworks, improving operational traceability; implemented access controls and backup strategy to reinforce security and continuity; and coordinated integration and validation with providers, ensuring consistency and quality in deliverables.

Provide mentorship to professionals on building scalable pipelines, optimizing SQL queries, and applying best practices in DataOps and governance. Contributed to strengthening the Data Engineering and Cloud talent ecosystem in Peru.

Designed cloud pipelines and MLOps strategies in GCP with Docker. Facilitated and coordinated a data engineering team in collaboration with the Analytics area under Agile methodologies, implementing governance practices and cost optimization. Managed automated model life cycles and promoted best practices for effective and innovative solutions. Optimized models with the inclusion of new variables via web scraping and REST APIs.

Designed and built Machine Learning pipelines in GCP, integrating code repositories to optimize DevOps and MLOps. Implemented automatic end-to-end processes in scalable architectures, covering all phases of the ML model life cycle. Led the architecture chapter and provided guidance on cloud guidelines to ensure best practices were applied.

Optimized data flows using DevOps and DataOps best practices. Productionized extraction, transformation, and loading processes for structured and unstructured sources using Python programming and ML model training. Designed efficient cloud architectures and configured GCP services for various digital transformation projects, integrating with the holding company's corporate solutions.

Implemented ETL processes for structured and unstructured sources using Python programming. Designed architectures and configured AWS services for various digital transformation projects. Applied best practices for automated deployments and monitoring.

Database administration, ETL processes, monitoring, process optimization, data analysis, server review, and reporting in .NET.