About
About me
I’m a data engineer with a background in data systems and analytics, and I’ve been working in the field for several years. More recently, my work has focused on blockchain data, especially EVM-compatible chains, where I build pipelines and analytics around on-chain activity. Lately, I’ve been deep into agentic engineering — building with AI agents, experimenting with new workflows, and having a lot of fun figuring out where it can go.
Outside work, I make music: I play guitar and bass, and I sing. I love RSS and use it to keep up with the things I’m interested in. I’m also learning Japanese because why not.このウェブサイトを見てくれてありがとうございます。
Background
Work and education.
A closer look at the systems I have worked on, the teams I have supported, and the foundations behind my data engineering practice.
Work
Production data systems, Web3 infrastructure, and applied ML.
Feb 2023 - Jan 2026
Data Engineer · kpk
Built, operated, and extended daily on-chain data pipelines tracking positions across 30+ DeFi protocols and supporting treasury reporting for DAOs including ENS, Gnosis, CoW, Nexus, Balancer, dYdX, and Arbitrum.
Developed Python services to extract, normalize, and enrich balances, protocol positions, rewards, and price feeds from RPC endpoints, oracles, protocol logic, and external APIs, then modeled the results in BigQuery.
Audited treasury reports end to end and improved reliability and observability through simpler processing, alerting, and structured logging. I also co-built a service that decoded raw EVM transactions, traces, and logs into structured financial events using GCP and PostgreSQL.
Implemented protocol-specific EVM indexing pipelines with Subsquid and TypeScript, working across ingestion, transformation, data quality, and reporting rather than treating them as separate problems.
Sep 2020 - Jun 2022
Deep Learning Engineer · YData
Prototyped generative models for synthetic tabular and time-series data, translating GAN-based research into working code.
Built evaluation metrics and Kubeflow pipelines to assess synthetic-data quality, and contributed to internal and open-source Python tooling.
Worked across GAN and probabilistic approaches, turning research ideas into experiments that could be compared, evaluated, and reused.
Education
Analytics, computer science, and the methods behind the work.
2019 - 2021
M.Sc. Advanced Analytics
Master’s degree in Data Science and Advanced Analytics. Coursework included Python data science, SQL/NoSQL databases, data mining, machine learning, natural language processing, genetic programming, deep learning, and visualization.
Thesis: Hyperparameter Search of a WGAN through Genetic Algorithms.
2016 - 2019
M.Sc. Economics & Business Informatics
Economics and Business Informatics in Pescara. Coursework included object-oriented programming in Java, statistics, algorithms and data structures, SQL databases, and R-based data mining.
Thesis: EDA and Bigram Analysis of a Clothing E-commerce.
Skills and tools