Data Engineer

Síntese de Qualificações

Data Engineer with experience in developing and operating data pipelines using Python, SQL, dbt, and Apache Airflow. Strong background in data modeling (staging, intermediate, and marts), SQL based data transformation, and data model documentation. Experienced in collaborating with business and technology teams to deliver scalable solutions focused on performance, governance, and data reliability. Hands-on professional with strong autonomy, technical curiosity, and a continuous learning mindset in open-source technologies and data architecture.

Experiência Profissional

• Data Engineer

  Responsibilities:
  -Design, develop, and maintain scalable ETL/ELT pipelines using Python, SQL, dbt, and Apache
  Airflow.
  -Build and maintain analytical data models following Medallion Architecture (Bronze, Silver, and Gold).
  -Develop fact and dimension models to support business intelligence and analytics.
  -Implement data transformation processes with a strong focus on data quality, governance, and
  performance.
  -Optimize SQL queries and data structures to improve processing efficiency and reduce execution time.
  -Monitor production pipelines, troubleshoot failures, and resolve data quality issues.
  -Collaborate with business stakeholders, analysts, and engineering teams to deliver scalable data solutions.
  Key Achievements:
  -Reduced dbt job execution time by 2853 through strategic materialization of intermediate and staging models
  -Implemented a Snowflake clustering strategy, analyzing Query Profile and micro-partition patterns, reducing query response time by 8 23 on key analytical tables
  -Developed and maintained pipelines orchestrated with Apache Airflow, transformed in dbt, and loaded into Snowflake, processing 50M records/day
  -Redesigned data models by granularity, decomposing a Purchase Order table into PO Header, PO Item, and PO Detail, reducing processed data volume and optimizing dashboard load times
  -Modeled dimensional data (fact/dimension) including materials, inventory, movements, and
  vendors following a medallion architecture (bronze/silver/gold) for BI and Analytics Engineering teams
  -Built reusable dbt macros to standardize transformations, reducing rework and increasing
  consistency across data models
  -Migrated views from SAP HANA to SAP Datasphere, building a layered architecture (raw, silver, gold) with wrapper views to preserve existing logic and minimize rework.

Formação Acadêmica

• Superior (3/2012 a 1/2020)

  Bachelor of Electronic Engineering - Federal University of Juiz de Fora (UFJF)

Cursos e Certificações

dbt Fundamentals October 2024
Snowflake Hands-On: Data Warehousing October 2024
Exploring SAP Datasphere January 2025

Conhecimentos Gerais

Data Engineer with experience in developing and operating data pipelines using Python, SQL,
dbt, and Apache Airflow. Strong background in data modeling (staging, intermediate, and marts), SQL
based data transformation, and data model documentation. Experienced in collaborating with business
and technology teams to deliver scalable solutions focused on performance, governance, and data
reliability. Hands-on professional with strong autonomy, technical curiosity, and a continuous learning
mindset in open-source technologies and data architecture.