Kauai Staingel

Kauai StaingelSoftware + Data Engineer

Software and data engineering for automation, integrations, and web data extraction.

I work across backend systems, automation, web data collection and cloud integrations.

  • 5,300hof manual work automated per month
  • 30M+requests executed and handled in production
  • 100%of execution-request tickets eliminated
  • 250K+data rows transformed into dashboards

Work that became real.

Selected projects, their technical footprint, and the shortest path to explore them.

  1. Nossa Mentoria

    Featured case

    A technology mentorship platform designed to connect mentors and mentees.

    Web · Supabase

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    Context
    The platform brings technology mentors and people seeking mentorship into one environment.
    Problem
    Mentors and mentees need a direct way to find each other and organize a mentorship relationship.
    Role
    I conceived the project and worked as its developer.
    Technical approach
    A web platform focused on discovery and connection between both sides of a technology mentorship.
    Nossa Mentoria landing page with a bright green background and stacked mentorship plan cards.

    Image 1 / 2

    Nossa Mentoria landing page and mentorship plan overview.
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  2. Solta a Voz

    Web

    A customizable communication app for non-speaking autistic people, paired with a monitoring dashboard for caregivers.

    Web · Backend · Data

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    Context
    The project was developed as a university capstone project with a mobile experience and a web application.
    Problem
    Non-speaking autistic people need communication tools that can adapt to their individual routines and vocabulary.
    Role
    I conceived the project and worked as its developer.
    Technical approach
    A personalized communication app supported by a dashboard where caregivers can follow its use.
    Solta a Voz mobile home screen with learning and bathroom communication categories.

    Image 1 / 3

    Custom communication categories on the mobile home screen.
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  3. AI Support Ticket Analyzer

    Automation

    An AI-assisted analyzer that reviews support interactions, resolution status, and key service-quality criteria.

    Automation · Data · Python

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    Context
    The analyzer was designed for reviewing completed support interactions.
    Problem
    Support interactions require a consistent review of how the service unfolded and whether the reported issue was resolved.
    Role
    I conceived the project and worked as its developer.
    Technical approach
    An AI-assisted analysis flow that evaluates each interaction and assigns scores to key review points.
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  4. RPA Portal

    Automation

    A portal for managing live automations, logs, errors, and operational dashboards from one place.

    Automation · Web · Data

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    Context
    The portal centralizes the operational monitoring of running automations.
    Problem
    Automation teams need a consolidated view of executions, failures, logs, and operational indicators.
    Role
    I conceived the project and worked as its developer.
    Technical approach
    A management portal where operations can run automations directly, with real-time execution visibility, error and log tracking, and integrated dashboards.
    Verified result
    Giving the operations team direct access to run automations is estimated to save the team 50 hours of manual work per month.

    Evidence note

    Estimated team time saved per month
    50 h/month
    RPA Portal landing page presenting services, automations, and operational dashboards for Lumma.

    Image 1 / 4

    RPA Portal entry point for services, automations, and dashboards.
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All repositories

A career path shaped by systems and operations.

Roles are grouped by company so changes in responsibility remain visible without repeating the same context.

  1. Lumma Despachante

    2 roles

    1. Present

      Development Coordinator

      Contribution and technical context

      Technical leadership across software delivery, development standards, architecture, automation, and delivery governance.

      Key contributions
      • Coordinate technical direction and delivery governance across software development work.
      • Implement engineering rules and shared standards for GitHub workflows, documentation, Clean Architecture, pull requests, and code reviews.
      • Guide the evolution of automations and continuous improvement of engineering processes.
      Impact
      • 30% reduction in automation-adjustment tickets after improvements to development standards and processes.
      • Elimination of 100% of automation-execution request tickets after the RPA Portal was expanded to run automations directly.

      Verified technologiesTechnical leadership · Agile practices · Code review · Delivery governance

    2. Software Engineer

      Contribution and technical context

      Backend and web systems built with Node.js, Python, React, Next.js, and NestJS, including APIs, web data collection, monitoring, and AWS services.

      Key contributions
      • Design and develop the RPA Portal to centralize automation monitoring, execution status, and error logs.
      • Build and maintain backend and web systems with Node.js, Python, NestJS, Next.js, and React.
      • Develop REST API integrations and structured web data collection flows.
      • Support processing, storage, orchestration, and monitoring with AWS Lambda, S3, RDS, and Step Functions.

      Verified technologiesPython · Crawlers · Requests · Axios · PostgreSQL · Node.js · NestJS · REST APIs · Express · AWS Lambda · Amazon S3 · Amazon RDS · AWS Step Functions

  2. SHOULDER

    1 role

    1. Software Engineer

      Contribution and technical context

      AI-assisted support-ticket classification workflow, browser automation, and web data collection with Selenium and Puppeteer.

      Key contributions
      • Design and implement an AI-assisted workflow for support-ticket classification and evaluation.
      • Develop browser automations and web data collection flows with Selenium and Puppeteer.
      • Maintain and improve RPA workflows used in operational support routines.
      Impact
      • 95% reduction in spending on a third-party ticket-evaluation tool after implementing the AI-assisted workflow.

      Verified technologiesPython · Crawlers · Selenium · Puppeteer · AWS Lambda · Amazon S3 · Amazon RDS · AWS Step Functions

  3. Xpeer

    1 role

    1. Management Information Systems Analyst

      Contribution and technical context

      Management information flows supported through SQL views and procedures, RPA, Power BI, and Python integrations.

      Key contributions
      • Develop SQL views and procedures that structure management information flows.
      • Build Power BI reports and dashboards from operational data.
      • Connect Python and RPA integrations to reduce repetitive steps and improve data processes.

      Verified technologiesPython · SQL · Power BI · Pandas

03 / Toolkit

Tools behind what I build.

A direct view of the technologies I use, organized by the role they play in projects and professional work.

ETL

Data collection, extraction, and integration workflows.

Data

Querying, transformation, reporting, and operational data analysis.

Engineering

Backend services, integrations, and maintainable APIs.

Leadership

Technical coordination, team practices, and delivery governance.

Cloud + infrastructure

AWS services used to process, store, and orchestrate application data.

About

I work where software, data, and operational problems meet.

I am a Software and Data Engineer focused on backend systems, automation, integrations, and web data collection. My work connects information flows with the systems and teams that rely on them.

From operational data to software architecture

My path began with reporting, SQL, and process data. It expanded into RPA and web data collection, backend and cloud systems, and, more recently, software architecture and technical coordination.

Why these problems matter to me

I am most interested in work that removes repetitive steps, connects fragmented systems, and makes data easier to collect and use in day-to-day work. The recurring goal is to turn an operational problem into a flow that can be understood, monitored, and improved.

Academic foundations behind the practice.

Formal education presented with only the course, degree, institution, and dates confirmed by the source.

  1. Bachelor's degree in Computer Science

    Institution
    Universidade Municipal de São Caetano do Sul (USCS)
    Period
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