Assigned as a Data Engineer to BCP (Banco de Crédito del Perú), the largest bank in Peru. Responsible for building data pipelines in Databricks for the company's data models. Developed and deployed business logic in PySpark and SQL, often integrating machine learning models. Managed the maintenance of production workflows. Utilized Azure tools such as Databricks, Azure Functions, Azure Key Vault, Azure Data Factory, and Jenkins for pipeline orchestration, secret management, service deployment, and CI/CD automation. Employed SonarQube, Fortify, and JFrog Xray for code quality, security, and compliance. Collaborated cross-functionally with clients and business units to understand requirements and deliver reliable, high-quality data products.

Provided global support to all business units, including international travel and conducting meetings in English with company suppliers. Led the migration of the enterprise data warehouse from PostgreSQL to Snowflake (provisioned on Azure). Participated actively in designing and modeling the data architecture, building layered data pipelines (staging, bronze, silver, gold) using dbt (with Jinja templates), Coalesce.io, and GitHub Actions for CI/CD, implementing incremental and modular (CDC) models. Integrated OpenMetadata for lineage traceability, data quality monitoring, and automatic documentation. Contributed to the development of data governance manuals, data modeling, and software development policies, emphasizing security best practices like Service Accounts (SA) with KeyPair, sensitive data masking, and Role-Based Access Control (RBAC). Managed data ingestion and orchestration from databases like SAP/HANA, Oracle, and Fabric using Apache Airflow, Aecorsoft, and FastAPI, with a focus on design patterns for modular and scalable DAGs. Developed technical Power BI dashboards to monitor DAG failures, pipeline anomalies, and key operational metrics. Understood the planning and supply chain (primary and secondary) of the company's beverages for data modeling.

Assigned to Rimac Seguros, the largest insurance company in Peru, operating within a multi-cloud architecture (AWS and GCP). Participated in projects that collectively generated over $33M in client benefits. Technically led the data engineering team, reporting progress, identifying potential blockers, and providing technical support. Communicated actively with stakeholders to understand business requirements, performed data mapping and analysis, and proposed customized solutions on both cloud platforms. Designed and maintained streaming pipelines in AWS using Amazon MSK (Kafka) with Apache Flink for real-time event processing, managing high-performance data streams from the company's mobile application. Built event-driven architectures in GCP using Pub/Sub (Kafka) and Dataflow (Apache Beam) to ingest and process high-volume prospect data from multiple sources, consolidating them in BigQuery for analytical consumption. Responsible for data modeling and developing technical proposals to integrate various data sources like SAP, Salesforce, and RPAs with Google Cloud. Performed analyses on internal client databases to develop business logic, building unified Data Warehouses subsequently loaded into Salesforce. Developed a public source scraper using Docker containers deployed via Cloud Run, integrating results directly into BigQuery, with containers managed by Terraform. Implemented data ingestion from SFTP servers with information from external providers to BigQuery, utilizing Dataflow and Cloud Functions. Developed monitoring dashboards in Power BI, integrating report generation with GCP via Airflow (DAGs) and Power Automate. Technologies used include: Amazon MSK (Kafka), Apache Flink, Redshift, Lambda, S3, EC2, BigQuery, GCS, DataFlow (Apache Beam), Pub/Sub, Cloud Run, Cloud Functions, Airflow (PySpark), DAGs, Docker, Python, BeautifulSoup, Pandas, Power BI, Power Automate, Terraform, Git, Jenkins, GitHub.

Led the development and maintenance of large-scale data extraction pipelines, migrating data from isolated SCADA servers and on-premise databases to cloud environments via batch processing. Implemented web scraping techniques to integrate external data sources, consolidating internal and external data into real-time dashboards using Power BI and Looker Studio. Tools used include SQL Server, MySQL, network protocols, and Google Cloud Platform. Member of the Data Analytics team, supporting the development and deployment of artificial intelligence models using MLflow for model lifecycle management. Designed and deployed an ARIMA time-series forecasting model to predict failures in hydroelectric power plant cooling systems. Developed a deep learning model leveraging CCTV systems for automatic fall detection of workers in hydroelectric power plants. Responsible for the administration and maintenance of SCADA systems (E-Terra and Pi System) and databases, managing internal processes and ensuring plant connectivity via RTUs, PLCs, and Data Gateways. Additionally, performed signal modeling, HMI design, and technical plant visits.

Worked on the 'Pullman' project for the international hotel chain, aimed at reducing tax reporting operational times and standardizing their internal database. Developed custom ETL flows for the extraction, transformation, and massive loading of data from diverse internal sources (XML, CSV, databases, Azure) to external web services of tax authorities, significantly optimizing client data management. These flows automated manual tasks that previously required 3-4 days of operator effort, reducing execution time to approximately 10 minutes. Utilized Python, Pandas, SAP, SQL, APIs, web authentication methods (OAuth2), and web scraping techniques to integrate and automate data ingestion processes. Maintained continuous communication with internal teams and clients to ensure compliance with technical and business requirements.