Data professional with strong foundations in Data Engineering, specializing in building scalable, production-grade data pipelines and analytical datasets.

I work with the modern data stack, focusing on modular SQL transformations (dbt-style), ELT pipelines, and orchestrated workflows in cloud environments (AWS & GCP). My goal is to transform raw data into reliable, well-modeled datasets that enable self-service analytics and drive business impact.

Currently working across domains such as logistics, marketing, CRM, and credit analytics.

🎓 MBA in Data Science & Analytics — University of São Paulo
🎓 PhD in Music Cognition

• Data Modeling & Analytics Engineering
• Advanced SQL & ELT Pipelines
• Python for Data Processing & Automation
• Workflow Orchestration (Airflow)
• Databricks & Spark
• AWS & GCP
• Data Quality, Testing & Observability
• BI & Semantic Layer (Looker, Power BI)

• Data: SQL (Redshift, BigQuery, PostgreSQL), Python
• Processing: Databricks, Pandas, PySpark
• Orchestration: Airflow
• BI / Modeling: Looker, LookML, Power BI
• Cloud: AWS (S3, Redshift), GCP
• Other: Git, Linux

• LinkedIn: https://www.linkedin.com/in/eduardo-k-s-mello/
• Email: eduardoksmello@gmail.com -->