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Achievement: StarstruckAchievement: QuickdrawAchievement: Pull SharkAchievement: YOLOAchievement: Pair Extraordinaire

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joycequoos/README.md
joyce.data — Data Engineering & Applied AI

✦ About

Data Engineer with a background in QA and Business Analysis. I treat data quality and integrity as part of the design, not a final checklist.

Current focus: data pipelines and SQL rules for fraud detection, feeding analyst work queues. Reports and dashboards for business visibility.

Stack: SQL, Python, AWS, Databricks, ELT/SSIS, .NET (C#) APIs, Azure DevOps. Currently applying AI to reduce false positives in transaction monitoring (AML).

Background: technical support (2005) → QA and Business Analysis on critical financial systems → Data Engineering (2020–present). This path shapes how I work: technical execution paired with direct problem discovery — with clients or teammates.

Open to industries beyond finance.

I document my learning publicly — every repository here is a step, not just a final result.

→ See the full portfolio, with solution case studies: joycequoos.github.io

✦ Stack by Domain

Data Engineering

SQL Server
ETL/SSIS
Python

*IA & Automation

Claude AI
Gemini
.NET

BI & Analytics

Power BI
Jupyter
Storytelling

Azure DevOps

Docker

Airflow

Databricks

✦ Real Problems, Delivered Solutions

Three snapshots from the AML (Anti-Money Laundering) case — from the ingestion pipeline to alert prioritization. → See the full storytelling


01 Pipeline de ingestão de Dados

**Problem:**ach client or data source presents a different access scenario — raw files, relational databases, cloud storage volumes — and the same ingestion technique isn't always the most efficient or feasible across all cases.

Solution: ETL and ELT pipelines adapted to each source:

  • SSIS — package orchestration in SQL Server environments
  • Python — custom, flexible ingestions
  • Bulk Insert — high-volume loads with performance in mind
  • View reads — direct extraction from the client's database
  • AWS/Azure — direct reads from cloud storage volumes
  • Airflow (DAGs) — orchestration and scheduling for data loading pipelines
  • APIs — reading JSON files, direct integration via API

8 técnicas ETL & ELT

02 Suspicious Transaction Detection Rules Engine

Problem: manually checking every transaction against the Compliance threshold doesn't scale with daily operation volume. Solution: an automated rule that flags transactions above the defined parameter and segregates the results into a dedicated table, creating a work queue for the Compliance team.

95 5

03 Alert Prioritization with SQL + Python

Problem: with dozens of alerts generated daily, Compliance needs to know where to start the investigation. Solution: a Python↔SQL Server connection (pymssql) to query alerts, rank clients with the highest incidence, and cross-reference transaction volume with product risk.

15 Corretora

✦ Learning & Projects

Area Description
Data (Engineering, Science/AI, Analysis) Data Engineering, Data Science / AI track, and Data Analysis
Web Development .NET, Angular, HTML, CSS, JavaScript and other Web Development content
Software Testing / QA Studies and practices in test planning, execution, reporting, and automation.

Exclusive AML Content

Additional materials, available separately, AML: Exclusive AML Content

Let's Talk?

Collaborations and new connections in Data Engineering and AI.

LinkedIn
GitHub
Email


✦ joyce.data — pipelines e IA para problemas reais

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  1. joycequoos joycequoos Public

    19 3

  2. SQL SQL Public

    Examples of Scripts: (DDL,DML,Views, Procedures, Functions)

    TSQL 8 3

  3. Principal_Data Principal_Data Public

    Principal_Data

    1

  4. Data_Enginer Data_Enginer Public

    Data Engineering study repository featuring notes, insights, ETL/ELT pipelines, orchestration, cloud practices, and hands-on projects using Python, Big Data tools, and Git.

  5. DataScience DataScience Public

    AI & Data Science Playground Personal portfolio and study repository focused on Artificial Intelligence and Data Science. Featuring hands-on implementations, predictive modeling, data pipeline inte…

    1

  6. Development Development Public

    Hands-on Web Development repository featuring practical studies, exercises, and projects built with .NET, JavaScript, Node.js, and modern web technologies.

    3