Experience
Data Engineer · Eggersmann Gruppe GmbH
May 2025 – Present · Germany
Lead data, cloud and database architecture, owning the AWS and databases infrastructure.
Defined the infra roadmap, implemented Data Architecture and Data Governance best practices in AWS, and actively contributed to hire and mentor engineers
Reduced database costs by 20% and sped up analytical queries by up to 5x. Almost no growth in services cost, despite 2-3x increase in the data ingested
Delivered data solutions and run the ETL service for the dowsntream (internal and external) consumers. Settled IaC (CloudFormation/CDK) deployments
stack: Python (Pandas, Polars, OOP) · AWS · PostgreSQL · TimescaleDB
Data Engineer · Thinksurance
Sep 2023 – Apr 2025 · Frankfurt am Main, Germany
Development, maintenance and optimization of ETL processes
Ensured data availability and integrity to drive key business insights and decision-making for customers
Migrated 400+ Hive Data Warehouse tables, 10x speed-up in daily ETL processes and a 30% reduction in incidents and response time
stack: Python (Pandas, OOP) · MySQL · Hive · Trino · Presto · AWS · Hadoop · Starburst Galaxy
Big Data Cloud Developer · EDP Comercial
Dec 2021 – Jul 2023 · Lisbon, Portugal
Developed, optimized and deployed Data Science and Analytics algorithms for the EDP Solar platform (~100k customers)
Predicted unknown characteristics for 1000s+ solar panels via a cost-optimized automatic routine using EC2, Machine Learning and time-series data
stack: Python (NumPy, Pandas, scikit-learn) · AWS · SQL
Education
PhD candidate in Mathematical Sciences (not concluded)
Queen Mary University of London
Sep 2020 – Sep 2021 · London, United Kingdom
MSc in Physics Engineering
Instituto Superior Técnico – University of Lisbon
Sep 2017 – Sep 2019 · Lisbon, Portugal
Theroretical Physics specialization
Master Thesis: "Strong lensing of light and shadow of a Black Hole surrounded by a heavy accretion disk"
BSc in Physics
University of Porto – Faculty of Sciences
Aug 2014 – Aug 2017 · Porto, Portugal
Publications
Brief resume: Implementation of an adaptive-step Runge-Kutta-Fehlberg method in Python to propagate photons in a (strong-gravity) curved spacetime around a black hole.
Certification & Courses
AWS
AWS Certified Developer – Associate
AWS Certified Cloud Practitioner
Coursera
Deep Learning Specialization by DeepLearning.AI
Machine Learning by Stanford University
Microsoft
Azure Data Fundamentals
Skill stack (resume)
Python (NumPy, Pandas, scikit-learn) for development and data manipulation
Cloud development in AWS for deploying and operating data products end to end
Vast SQL and NoSQL for querying large datasets efficiently, including MySQL, PostgreSQL, Trino and others;
ETL orchestration with Airflow
Technical Skills
Programming Languages
Python, SQL (MySQL, Hive, Presto, Trino), NoSQL, R, Mathematica, Bash
Developer Tools
DataGrip, Docker, Git, GitHub, GitLab, VS Code
Libraries
Pandas, NumPy, Airflow, SciPy, scikit-learn, Matplotlib, PyTorch, Polars, TensorFlow
Others
AWS Cloud, Command Line / Shell, Hadoop, Nifi, LaTeX, MongoDB, Starburst Galaxy, Spark, macOS, Linux, Windows