Giovanni Bortolussi

Giovanni Bortolussi

Data Engineering Manager / Italy

Currently leading my team's transition into the AI era

I'm based in Italy and manage a data engineering team in India. Most of my energy goes into helping them grow across time zones and cultures while keeping our data reliable and trustworthy. Right now we're focused on building a self-service data engineering platform powered by loop engineering (agents working in tight, self-correcting build–test loops) and AI agents, so the rest of the company can get the data they need without waiting on us and the team can move up the stack: from maintaining pipelines to designing the systems behind them.

I got here the long way: mechanical engineering, a few years in sales, then a Master of Science in Business Administration with a specialisation in business analytics. It means I think about data problems from the business side first and the technical side second.

Stack

  • AI Agents
  • Claude Code
  • MCP
  • dbt
  • Snowflake
  • Superset
  • Airflow
  • Azure
  • Terraform
  • Docker
  • GitHub Actions
  • Python
  • Grafana
  • Datadog

Projects

  • Wiring AI into how the team works: from writing dbt models to reviewing PRs to debugging pipelines. The goal isn't to replace the engineer's judgement but to remove everything around it that doesn't need it.

  • Automated ETL that uses AI to process both structured and unstructured sources at scale, turning messy inputs into clean, queryable data.

  • An end-to-end observability solution that surfaces where Snowflake spend goes, down to the query and user level, so the team can stay fast without burning credits on waste.

  • Multi-cluster Airflow setup with dbt transformations and compliance requirements handled at the infrastructure level, not bolted on after.

  • Multi-environment CI/CD pipelines with robust testing and automation, backed by Terraform-managed infrastructure for zero configuration drift.

  • Standardised data modelling, testing, and governance across every project: the foundation that makes our data reliable and trustworthy.

Seminars & Talks

  • Guest seminar at the University of Udine on how AI is reshaping the data engineer's role: from building pipelines to architecting intelligent systems that accelerate development, automate governance, and make infrastructure smarter. LinkedIn post

  • Guest seminar at the University of Udine for the Advanced Data Science course, bridging academic concepts and production reality with Meltano, Airflow, and Kubernetes. LinkedIn post

  • Podcast interview on Huroes Talk (in Italian) about data engineering practices and how to build a data-driven culture inside a company. Listen on Spotify