Senior Data Engineer
About Me
I am a results-driven Senior Data Engineer with over 8 years of experience in designing scalable architectures, building high-throughput pipelines, and delivering actionable insights through advanced analytics. I have a proven track record in ETL development, data modeling, and cloud platforms such as AWS, GCP, and Azure, with strong proficiency in SQL and Python. My experience includes deploying machine learning models, performing statistical analysis, and building intuitive data products that empower decision-making across engineering, product, and executive teams. I am known for resolving complex data issues, optimizing workflows, and leading cross-functional collaboration to drive innovation. Currently, I am actively pursuing C2C-based remote opportunities with global teams, contributing to modern data engineering initiatives while working from Brazil.
Skills
PythonSQLAWSDockerAzureCI CDMachine LearningGCPGitData AnalyticsAgileMicrosoft ExcelDevOpsA B TestingScrum
Education
Postgraduate in IT Governance
Expected to complete in 12/2025
Postgraduate in Data Science
Completed in 2025
Bachelor's in Systems Analysis and Development
Completed in 2024
Experience
Architected and deployed fault-tolerant, high-performance data pipelines using Apache Spark and AWS Glue, accelerating analytics delivery by 60%. Led migration from legacy systems to a cloud-native architecture, reducing operational costs by $1.2M annually. Translated business needs into scalable data models driving multimillion-dollar growth initiatives. Automated ETL workflows processing over 15TB/day with 99.9% uptime. Mentored 8+ engineers and introduced a centralized data governance framework that improved compliance by 85%.
Delivered real-time support and root-cause analysis for reporting systems, reducing downtime by 70%. Resolved data discrepancies across platforms, improving accuracy by 95%. Implemented validation scripts reducing manual review by 60%. Optimized SQL procedures, cutting report generation time from 15 to 3 minutes. Translated stakeholder issues into technical fixes, increasing satisfaction by 40%.
Built ML models using Python and Scikit-learn that boosted customer retention by 35%. Processed 100M+ records using SQL and R, enabling predictive insights. Designed A/B testing frameworks, increasing conversion by 22%. Created dashboards (Power BI/Tableau) for KPI tracking. Led full-cycle DS projects contributing $2.5M+ in revenue growth.
Built scalable data pipelines with Python and Airflow, improving delivery speed by 55%. Integrated 10TB+ data from APIs, flat files, and cloud sources into a unified lake. Optimized ETL and SQL logic, reducing compute costs and processing time by 70%. Deployed data warehouses with Snowflake and Redshift. Supported ML and analytics teams with reliable data flows.