Fernando Hocevar

About Me

I am a Principal Software Engineer, Tech Lead and Full Stack Developer with more than 20 years of experience in software development, architecture and technical leadership.

I work with APIs, microservices, enterprise integrations, data engineering, artificial intelligence, operational automation, DevOps and observability. I have experience with mission-critical environments, ETL pipelines, SAP integrations, Jenkins, Docker, Kubernetes, relational databases and cloud solutions.

This portfolio showcases practical projects focused on real-world engineering challenges, including AI-powered prescriptive maintenance, geospatial data processing, financial systems, enterprise e-commerce, epidemiological intelligence, capacity management, SAP integration, pipeline orchestration and observability.

Core Technology Stack

Featured Projects

AI / Machine Learning / RAG / Full Stack

Prescriptive Maintenance Enterprise

Full Stack AI platform for prescriptive analysis of industrial assets, combining operational data, Machine Learning, vector search and technical documentation to generate maintenance recommendations.

• Python, FastAPI, PostgreSQL, pgvector and Redis
• Isolation Forest for anomaly detection
• Embeddings, vector search and RAG architecture
• Interactive dashboard for asset analysis
• Clean Architecture, DDD and SOLID
• Docker, automated testing and observability
• Processing of more than 166,000 operational events

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Geospatial / Data Engineering / Backend

Parcel + Zoning Data Platform

Platform for ingesting, normalizing and analyzing parcel and zoning geospatial data, integrating ArcGIS services with PostgreSQL/PostGIS and a REST API built with FastAPI.

• Python, FastAPI, PostgreSQL 16 and PostGIS
• Ingestion of more than 120,000 parcels
• Integration with ArcGIS services
• Spatial joins between parcels and zoning areas
• Geometry-based area calculations
• Idempotent data processing pipeline
• Spatial queries and statistics through REST APIs
• Automated testing with Pytest
• Containerized environment with Docker Compose

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Full Stack / Financial Systems

Financial Accountability MVP

Full Stack platform for financial control, traceability and accountability, designed with a focus on business-rule organization, data consistency and operational auditability.

• API-based Full Stack architecture
• Financial operation control and validation
• Traceability and operation history
• Structured database persistence
• Separation of business rules and presentation
• Architecture prepared for external integrations

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Java / React / Distributed Systems / Full Stack

Enterprise E-commerce Platform

Full Stack e-commerce platform built with a Java backend and React frontend, designed around enterprise architecture patterns, transactional consistency and reliable asynchronous processing.

• Java and Spring Boot with DDD, Clean Architecture and SOLID
• React frontend with product catalog, cart and checkout flows
• PostgreSQL persistence with Flyway migrations
• Redis-backed shopping cart
• RabbitMQ for asynchronous messaging
• Transactional Outbox Pattern for reliable event publishing
• Idempotency-Key support for checkout operations
• Pessimistic locking for inventory consistency
• JWT authentication and authorization
• Actuator, Prometheus, automated tests and GitHub Actions

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Java / Spring Boot / React / Full Stack

Booking Scheduler Enterprise

Full Stack booking and scheduling platform built with Spring Boot and React, featuring JWT authentication and persistent application data with PostgreSQL and Redis. The interface supports provider and service setup as well as booking creation, rescheduling and cancellation workflows.

• Java and Spring Boot backend
• React frontend for scheduling workflows
• JWT-based authentication
• PostgreSQL for persistent application data
• Redis integration
• Provider and service management
• Booking creation, rescheduling and cancellation flows
• Separation between backend API and frontend application

Backend Repository Frontend Repository

Python / FastAPI / Data Engineering / Public Health

Epidemiological Intelligence & Alerting API

Epidemiological data aggregation and alerting platform designed to ingest, normalize and analyze public health data, providing structured indicators, epidemiological bulletins and automated disease alerts.

• Python and asynchronous FastAPI architecture
• PostgreSQL with SQLAlchemy and Alembic migrations
• WHO epidemiological bulletin integration
• Dengue data ingestion and normalization pipeline
• Processing of more than 73,000 dengue records in a single ingestion
• Duplicate detection during data ingestion
• Epidemiological indicators by disease and geographic region
• Automated alert generation with severity classification
• Scheduled ingestion and asynchronous processing
• Docker-based environment and automated testing

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Orchestration / Data Engineering

Airflow Enterprise PoC

PoC using Apache Airflow to validate orchestration of critical pipelines, retries, fault tolerance, observability and distributed execution.

• Python, Airflow, Docker and PostgreSQL
• DAGs with failure handling and logging
• Architecture prepared for SAP, APIs and enterprise ETL

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Backend / Capacity Management

ITIL Capacity Management API

API for capacity management, inventory, dashboards and observability across enterprise environments, with Jenkins, Argo CD and PostgreSQL integrations.

• FastAPI, PostgreSQL, Docker and SQLAlchemy
• HTML dashboards and CSV/Excel/Parquet exports
• Capacity scoring, historical analysis and forecasting
• Jenkins and Argo CD integrations

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DevOps / Observability

Jenkins Capacity Dashboard

Dashboard for analyzing agents, executors, queues, jobs, failures and capacity trends across Jenkins environments.

• Automated data collection through the Jenkins API
• Utilization, failure and execution-duration indicators
• Operational history and data export
• Jenkins agent capacity analysis

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SAP

Integration / Automation

SAP RFC Automation

Python automation for executing and monitoring SAP jobs through RFC, focused on logging, timeouts, error handling and controlled execution through Jenkins.

• Python, PyRFC and Jenkins
• Status control and operational troubleshooting
• Error and timeout handling
• Foundation for RCA and SM37/ST22 analysis