- Systems + Business Process Analysis
- Workflow Process Design + Mapping
- Production Support / Troubleshooting
- Technical + Systems Documentation
- Data Flow Analysis + Optimization
- Vendor + Stakeholder Coordination
- Root Cause + Incident Investigation
Hi, my name is
Joshua Faria.
I build better business systems.
I enjoy understanding how businesses actually work. By mapping processes, connecting systems, and removing unnecessary friction, I build solutions that make everyday work simpler, faster, and more reliable.
01.About
I've always been interested in understanding how businesses actually work. Behind every product, service, or customer interaction is a network of people, processes, and systems working together.
I enjoy studying those systems and understanding how information flows, where inefficiencies appear, and why certain processes become more complicated over time. Once I understand the bigger picture, I look for practical ways to simplify it.
Whether that means improving a workflow, connecting systems, or redesigning a process, my goal is always the same: build solutions that are reliable, scalable, and make everyday work easier.
02.Experience
Cross Functional Technician → Automation / Integration Systems Ownership
@ Logistics Alliance
2024 — Present
- Owned and stabilized production automation workflows supporting shipment creation, dispatch routing, PO validation, and operational data movement across logistics systems.
- Built and maintained n8n workflows connecting Gmail, Monday.com, internal platforms, AWS-related reports, Google Sheets, and internal APIs.
- Troubleshot API and workflow failures using Postman, Swagger, JSON payload inspection, and production logs to restore operational continuity.
- Coordinated with internal operations, customer service, IT leadership, and external vendors to validate workflow changes and reduce production risk.
- Documented workflows, failure paths, and operator playbooks so automation could be understood, supported, and improved over time.
03.Selected Work
Production Validation Framework
Enterprise Data Validation System
Designed a production-grade validation framework that reconciled operational data against a trusted system of record, catching discrepancies before downstream impact. Replaced manual verification with automation that improved data quality, visibility, and risk control.
Business Impact
- 95% cache hit rate reducing redundant AWS API lookups
- 0.0% processing error rate across production runs
- Validation confidence improved from 87.0% to 99.7%
- 56,910 enterprise records validated across 40 operational runs
Intelligent Routing Framework
Automated Data Routing System
Designed a production workflow that routed operational data into standardized outputs using configurable business rules. Eliminated manual routing, improved processing consistency, and increased visibility across downstream systems.
Business Impact
- 34 business logic rules supported through automated routing
- 62,323 operational records processed across 30 production days
- 3,988 records processed during peak-volume workflow activity
- Resilient exception handling built across intake, processing, and output stages
- Fully automated workflow from source data ingestion to final delivery
Intelligent Decision Support
Machine Learning Prediction Platform
Built an end-to-end ML platform with automated feature engineering and explainable predictions. Unified ingestion, transformation, analysis, and delivery in one modular, production-ready pipeline.
Business Impact
- 62,000+ historical records transformed into model-ready inputs
- Automated ML workflow built across ingestion, feature processing, modeling, and output delivery
- Modular pipeline structure designed for retraining, tuning, and validation
- Probability-based decision signals generated from predictive model outputs
Cloud Integration Framework
Serverless Integration Platform
Designed and validated a serverless integration workflow that transformed operational data into standardized outputs through cloud processing, API validation, and environment-specific testing. Built for reliability, repeatability, and production readiness.
Business Impact
- Designed cloud-based integration workflows for structured data processing
- Validated API requests across DEV, QA, and PROD environments
- Standardized payload handling for consistent system communication
- Improved deployment readiness through repeatable testing and validation
Additional Systems & Automation Work
A collection of anonymized workflow automation and systems projects focused on data routing, API payload handling, cloud processing, structured reporting, workspace standardization, and exception handling.
Status Update Automation System
Designed an API-driven update workflow that monitors structured records, identifies recent changes, submits controlled update requests, and logs responses for operational traceability.
AWS - API PATCH - Workflow Automation - Data Updates - Audit Logging
Email-to-Workspace Intake Automation
Built an intake workflow that monitors labeled emails, extracts message metadata, routes attachments using recipient-based logic, forwards standardized outputs, and logs unmatched cases for review.
Gmail - n8n - Attachment Routing - Intake Automation - Exception Alerts
API Payload Validation Console
Created a controlled integration tool that converts spreadsheet inputs into structured JSON payloads, validates required fields, normalizes formats, removes invalid values, and supports API submission testing.
JSON - REST API - Data Transformation - Payload Validation - API Testing
Workspace Structure Automation
Automated standardized workspace/group creation from predefined configuration data, reducing repetitive setup work and improving consistency across team workflows.
Monday.com - n8n - Workspace Automation - Standardization - Admin Workflow
API Client Reliability Testing
Expanded API client functionality with additional endpoint methods and test coverage for successful responses, invalid inputs, HTTP errors, connection failures, and malformed JSON handling.
Python - Pytest - REST API - Unit Testing - Error Handling
Data Mapping Validation Prototype
Built a prototype service that validates incoming IDs, retrieves related API records, maps structured data objects, publishes outputs to a queue, and routes failures to a controlled error path.
Python - DTO Validation - API Integration - SQS - Error Handling
04.Contact
Got a messy workflow that needs fixing?
I'm looking for roles where I can own the space between operations and systems — the part where processes break, data gets messy, handoffs fail, and automation can actually make the business run better.
If you need someone who can investigate the problem, map the workflow, build the automation, test the edge cases, and keep improving it after it goes live, let's talk.