Backend Software Engineer focused on automation, API integrations, and scalable systems. I design backend services with Python, Node.js, SQL, and cloud APIs to connect fragmented business platforms into reliable operational workflows.
My recent work includes backend platforms supporting 8K-12K daily transactions, automation flows that removed ~3 hours/day of manual reporting per analyst, ETL pipelines that cut processing time by ~40%, and API optimizations that improved response times by 35-40%.
I operate across architecture, implementation, and systems governance to turn finance, operations, and reporting bottlenecks into measurable backend systems with real-world usage.
Professional Experience & Enterprise Environments
Loja do Sapo
Backend architecture, automations, integrations, and operational systems.
3 roles
Designed internal backend systems with Python and PostgreSQL to support 8K-12K daily transactions across operational workflows.
Architected GitHub Actions and API-driven automations that eliminated ~3 hours/day of manual financial reporting per analyst.
Built ETL pipelines across Google Cloud, Zoho, and third-party services, reducing data processing time by ~40%.
Delivered real-time dashboards, custom filters, and backend governance standards for multiple internal systems.
Developed REST integrations in Python and Node.js across 6+ core business systems spanning Google Cloud, Zoho, and external services.
Automated data extraction and enrichment workflows, reducing manual input and improving data accuracy in operational systems.
Applied caching and async processing to backend services, improving API response times by 35-40%.
Maintained AWS S3 and Lambda processes while enforcing backend rules for discounts, validations, and operational constraints.
Implemented 20+ automated workflows and business rules with Python and Deluge to reduce repetitive operational work.
Built reporting pipelines and data structures for real-time operational tracking and compliance visibility.
Developed validated processing flows that improved reporting quality and execution consistency.
iCaiu
Integration architecture, backend communication layers, and monitoring pipelines.
2 roles
Designed API-first integration architecture across 4+ platforms using AWS, Google Cloud, Zoho, and external services.
Automated financial and operational workflows, replacing spreadsheet-driven reporting with backend automation.
Built centralized dashboards and data pipelines for real-time business monitoring.
Defined authentication patterns, integration standards, and data-flow governance for external services.
Developed backend communication layers and Python REST integrations to improve data reliability across multiple systems.
Tested and debugged 15+ integration endpoints, removing critical automation bottlenecks.
Supported AWS EC2 and RDS infrastructure backing distributed backend services.
WR Auto Pecas
Operations systems, local automation, inventory tooling, and internal web support.
1 role
Developed 25+ Python automation tools for administrative and inventory processes, saving 30-35 hours per week.
Designed internal systems for inventory control, product tracking, and delivery management on local servers with cloud backup.
Maintained operational systems to preserve data accuracy and compliance across day-to-day operations.
Built and maintained internal web tools and the company website with HTML, CSS, and JavaScript.
Engineering Operating Model
Signal layerSystems stay readable when their signals stay visible.
Bounded Integrations
Clear contracts between APIs, workers, and storage
I keep provider-specific behavior at the edge so business logic remains testable, replaceable, and easier to reason about.
Replayable Data Flow
Raw payloads, normalized models, and audit trails
Ingestion is designed so failures can be inspected, corrected, and reprocessed without losing the original operational context.
Operational Feedback
Signals before surprises
Dashboards, logs, scheduled checks, and failure summaries help expose drift before it turns into hidden business risk.
AI-Assisted Delivery
Agent speed with engineering review
I use AI agents to accelerate exploration, scaffolding, and validation while keeping architecture, security, and production behavior under human review.
Core Backend Skills & Tech Stack
Languages & Core StackPythonJSJavaScriptAWSDelugeHTML5CSS3DockerSQL
