About
Accomplished Data Engineer with over 5 years of experience, specializing in architecting and optimizing scalable data pipelines and real-time data processing solutions. Proven track record in leveraging AWS, Terraform, and PySpark to drive efficiency, enhance workflows, and deliver actionable insights within complex cloud and big data environments.
Work
Critical Techworks - BMW Group
|Data Engineer & Scrum Master
Lisbon, Lisbon, Portugal
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Summary
Led data engineering initiatives and agile scrum processes, driving scalable data solutions and enhancing team efficiency within a dynamic cloud environment.
Highlights
Architected and deployed scalable real-time data ingestion and processing pipelines in AWS, leveraging Lambda, Glue, and S3 to ensure high data availability and integrity.
Developed comprehensive functional testing sets and a robust CI/CD pipeline with GitHub Actions, significantly improving deployment reliability and efficiency.
Built and maintained analytical tables on Apache Iceberg, adhering to best practices to optimize data accessibility and performance for critical business insights.
Automated infrastructure deployments using Terraform, reducing manual effort and accelerating deployment times for data solutions.
Drove team efficiency and alignment with BMW's data initiatives as Scrum Master, iteratively adapting delivery metrics and fostering continuous improvement.
BNP Paribas
|Data Engineer / Data Analyst
Lisbon, Lisbon, Portugal
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Summary
Designed and implemented robust ETL/ELT processes and analyzed large-scale datasets to generate actionable insights for credit risk management and regulatory compliance.
Highlights
Designed and implemented efficient ETL/ELT processes for critical credit risk datasets within a distributed HDFS environment, ensuring data integrity and availability.
Analyzed large-scale datasets using PySpark and Hive SQL, generating actionable insights crucial for EBA Stress Testing and other regulatory frameworks.
Developed interactive Tableau dashboards, empowering stakeholders to monitor key risk metrics and compliance KPIs, enhancing data-driven decision-making.
Celfinet
|Software Developer Intern
Lisbon, Lisbon, Portugal
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Summary
Developed an object-oriented Python application to automate mobile app testing, significantly reducing operational time.
Highlights
Developed an object-oriented Python application for automating app usage testing on iOS/Android devices, reducing testing time by more than 20%.
Education
Instituto Superior Técnico
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M.Sc.
Electrical and Computer Engineering
Grade: 16/20
Courses
Thesis: Time series analysis using restricted Boltzmann machines and dynamic Bayesian networks (Grade 18/20)
Télécom ParisTech
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ATHENS Programme
Université Catholique de Louvain
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Erasmus Programme
Languages
Portuguese
Native
English
Proficient
Spanish
Proficient
French
Proficient
German
Proficient
Skills
Cloud Platforms
AWS, Azure Data Fundamentals, Lambda, Glue, S3.
Programming & Data Tools
Python, PySpark, SQL, Apache Iceberg, Spark, Hive SQL, Tableau, Hugo.
DevOps & Orchestration
Terraform, GitHub Actions, Docker, CI/CD.
Methodologies & Data Management
Scrum, Agile, ETL/ELT, HDFS, Data Ingestion, Data Processing, Data Pipelines.
Machine Learning & AI
Neural Networks, Deep Learning, Generative AI (GenAI), Restricted Boltzmann Machines, Dynamic Bayesian Networks.