Juan Leiro

Designed and implemented advanced data architectures for tier-1 clients in the telecommunications and banking sectors, focusing on scalability and automation.

Engineered complex ETL pipelines using Python, ingesting data from multiple sources (SFTP, AWS S3, and 3rd-party APIs) into MongoDB and S3 for BBVA. Designed and managed Apache Airflow DAGs to automate data workflows and transformation into BigQuery views. Implemented data transfers using DataX, incorporating Google Cloud Functions for real-time data transformation before loading into BigQuery. Developed custom parsers for Google Chronicle using Apache NiFi and GCP Pub/Sub for high-throughput security event processing in cybersecurity data engineering. Collaborated on system architecture and developed robust APIs in Python for a specialized computer vision internal project. Managed multi-cloud environments using AWS (S3, Awsume) and GCP (Pub/Sub, BigQuery, Cloud Functions). Orchestrated containerized workloads with Docker and Kubernetes within GitHub CI/CD pipelines.

Led critical data migration and infrastructure modernization projects, transitioning legacy on-premise systems to scalable cloud architectures within a highly regulated banking environment.

Orchestrated the migration of large-scale financial datasets from on-premise servers to Google Cloud Platform

• • (BigQuery) and Azure, ensuring data integrity and zero-downtime. Designed and maintained production-grade APIs using FastAPI, implementing secure authentication and authorization layers integrating LDAP and Azure Active Directory (AD). Managed complex data structures across both NoSQL (MongoDB) and Warehouse (BigQuery) environments, handling sensitive production data with high-availability requirements. Deployed and managed containerized workloads using Docker and Kubernetes, streamlining the CI/CD pipeline through GitHub for automated deployments. Delivered frequent production updates and collaborated on system architecture refinements working under Agile frameworks.

Developed real-time testing frameworks for automotive electronic control units (ECUs), ensuring the reliability and performance of vehicle-integrated systems.

Designed and implemented a comprehensive testing suite to validate C++ firmware running on vehicle

• • hardware in real-time (Hardware-in-the-Loop - HIL). Developed the communication interface (Bridge) between the vehicle's hardware and the testing environment, enabling seamless data exchange and command execution. Authored and maintained automated test scripts using Python to validate hardware logic, improving testing efficiency and bug detection. Utilized Visual Studio across the full stack to debug and optimize the interaction between high-level software and low-level C++ code. Executed rigorous performance tests under real-time constraints to ensure automotive safety standards were met before production.