Fast lane
Guilherme Yuji Marcolongo Adania
Data Engineering · Data Analytics · BI · Automation
The essentials, in plain text with no animation. For the full ride, start the immersive version. Immersive version
Road signs
- 30xfaster
metadata briefing validation — 15k+ rows in minutes - 85xin continuous cycles
the same validation, running back to back - −70%daily check time
from 3–4 hours to under 1 hour - ~60incidents caught
in the first 4 months of monitoring - 70projects monitored
volumetry, load delays and SLAs - 15freelance clients
auto shops, optical stores and service companies
Summary
Data and BI professional with hands-on experience across data engineering, data quality, Python automation, SQL, REST APIs, Big Data, and data governance in enterprise environments. Experienced in designing and shipping internal data products end to end — from API integrations and validation engines to automated monitoring systems and reporting solutions — as well as building full-stack systems for external clients as an independent developer. Strong analytical profile with a practical Data Engineering mindset, focused on scalable, accurate, and maintainable solutions.
Experience
Junior Data Analyst · Engineering Brasil
Vivo Project
- Lead the Engineering Brasil initiative for creating AI agents and automation solutions for Vivo, working with Python, LangGraph, and multi-agent architectures to automate business workflows (initiative in early stage).
- Work in the Data Curation workstream for the Vivo project, supporting data organization, metadata, cataloging, governance, and quality processes.
- Designed and built a metadata briefing validation system integrated with Informatica EDC via REST APIs, using parallel HTTP requests and thread pooling. Validates assets, databases, tables, fields, descriptions, business names, and additional metadata attributes in a single run.
- ImpactBriefings above 2,000 rows were previously unfeasible or took hours on the legacy process; briefings above 15,000 rows now complete in minutes — approximately 30x faster for single validations and 85x faster for continuous validation cycles.
- Built an automated monitoring system covering ~70 multi-table projects that detects volumetry deviations, data load delays, and SLA breaches, replacing a fully manual daily check performed by two analysts.
- Impact~60 incidents detected in the first 4 months of operation; daily validation time reduced from 3–4 hours to under 1 hour (~70%).
- Extended the monitoring system with automated visual dashboard validation to catch silent refresh failures — dashboards that update without error but render blank or corrupted. Runs on a fixed intra-day schedule, exports the current dashboard state to PDF, converts it to PNG, and compares it against a reference image using OpenCV to flag anomalies. Built after a client-reported broken dashboard; has since flagged 2 real failures.
More details (5)Fewer details
- Perform Data Quality analysis, validation, monitoring, and troubleshooting across enterprise data processes, investigating inconsistencies in records, metadata, and technical documentation.
- Work with data cataloging, traceability, taxonomy, and governance processes to improve the organization and reliability of data assets.
- Collaborate with technical and business stakeholders to standardize processes, document requirements, and improve data quality across teams.
- Work with medallion architecture (bronze / silver / gold) and data domain organization within the project's data platform.
- Operate data workloads on GCP virtual machines within the enterprise environment.
Stack Python, SQL, Databricks, PySpark, Hive, Teradata, DBeaver, Power BI, Informatica EDC, REST APIs, GCP, Azure DevOps
Data Analyst · Cellere Soluções em TIC
Vivo Project
- Developed Python automations that reduced recurring manual work for analysts and improved operational efficiency.
- Created and maintained internal systems and data integrations between platforms through REST APIs and automated workflows.
- Performed data analysis and curation in Big Data environments, validating tables, fields, structures, and metadata at scale.
More details (2)Fewer details
- Wrote SQL queries in distributed Hive/Tez environments over partitioned tables for data validation, reconciliation, and cross-source analysis.
- Reviewed technical data briefings and translated requirements between technical and business teams, supporting data governance and documentation.
Independent Developer · Freelance
Software Development
- Delivered custom systems end to end for approximately 15 small and mid-sized business clients, including auto repair shops, optical stores, and similar service companies.
- Handled the full cycle: requirements gathering with non-technical clients, system design, development, deployment, and post-delivery support.
- Built web systems and internal management tools using PHP, Next.js, React, and TypeScript, containerized with Docker and deployed to VPS environments.
Skills
- Programming & Automation
- Python
- SQL
- JavaScript
- TypeScript
- PHP
- REST APIs
- Scripting
- Process automation
- Parallel processing / thread pooling
- Selenium
- OpenCV
- openpyxl
- Data Engineering
- ETL/ELT
- Data pipelines
- Data transformation
- Data integration
- Data quality
- QA/QC
- Medallion architecture
- Data modeling
- Partitioning
- Troubleshooting
- Root-cause analysis
- Data Platforms & Processing
- Databricks
- PySpark
- pandas
- Hive/Tez
- Teradata
- Big Data
- GCP
- Informatica EDC
- PostgreSQL
- Supabase
- Data Formats
- Parquet
- JSON
- CSV
- XML
- BI & Reporting
- Power BI
- Dashboard development
- Data visualization
- Recurring reporting workflows
- AI & Agents
- LangGraph
- Multi-agent architectures
- OpenAI APIs
- LLM-based automation
- Web & Frameworks
- Next.js
- React
- Flask
- FastAPI
- Streamlit
- HTML/CSS
- DevOps & Tools
- Docker
- Git
- Azure DevOps
- VPS deployment
- DBeaver
- Figma
- Data Governance
- Data Quality
- Metadata management
- Cataloging
- Taxonomy
- Traceability
- Governance
- Technical documentation
Spec sheet
The same skills, read as a car's spec sheet.
- Engine
- Python · SQL
- Transmission
- REST APIs · integrations
- Chassis
- Databricks · PySpark · Hive/Tez
- Onboard electronics
- LangGraph · AI agents · OpenAI
- Sensors
- Monitoring · data quality · OpenCV
- Dashboard
- Power BI · dashboards
- Bodywork
- Next.js · React · TypeScript
- Workshop
- Docker · Git · Azure DevOps · VPS
Education
Bachelor's Degree in Systems Analysis and Development
Universidade Presbiteriana Mackenzie
Systems Analysis and Development
FATEC — Transferred to Mackenzie
Technical Degree in Systems Development
ETEC
Glovebox · certifications
CS50x: Introduction to Computer Science
Harvard University ·
Data Engineering Foundations Professional Certificate
Astronomer ·
OpenAI & Python: APIs and Chatbots
Alura ·
Data Engineering with Databricks
Alura ·
Data Science
Alura ·
Machine Learning in Practice
Alura ·
Languages
Portuguese
Native
English
C2 (EF SET)
Contact
- Emailgyuji1904@gmail.com
- LinkedInlinkedin.com/in/guilherme-yuji-391033241
- GitHubgithub.com/GuiYuuji
- ServicesI also build custom systems, automations and dashboards for businesses.
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