Data Engineer · PySpark · Databricks · AWS

Hi, I'm Cato. I build data pipelines that turn messy sources into tables people trust.

Data engineer with 6+ years of experience building data integration pipelines for finance, insurance, mobility and marketing, from Spark on Hadoop to Azure Data Factory and BigQuery. My latest project is a pan-European company-registry lakehouse on Databricks and AWS: it keeps 52 million register rows up to date every month, and its results are live on this site.

Open to data engineering roles: full-time or contract, remote or on-site in Europe.

Experience with

  • Corum L'Épargne
  • RiverBank
  • Epsilon France (Publicis Groupe)
  • Mobilize Financial Services
  • PMU
  • Allianz France
Cato Perez

AWS Certified Cloud PractitionerNew

Amazon Web Services · earned October 2026

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Six national registers flowing through landing, bronze, silver and gold layers to a map

Live · Updated October 15, 2026

Pan-European Company Registry Lakehouse

Six national company registers (52 million rows) ingested, cleaned, historised and geocoded on Databricks serverless and AWS, then published as an interactive map and insights that refresh every month.

  • 52Mregister rows, refreshed monthly
  • 6national registers, one harmonised model
  • 97%of companies on the map, with free geocoding
  • ~200tests, all runnable on a laptop
What's inside
  • Ingestion with AWS Lambda and S3, scheduled by EventBridge and deployed with SAM through GitHub OIDC.
  • Medallion architecture on Databricks serverless: raw bronze, SCD Type 2 silver with one Delta MERGE per snapshot, Kimball gold.
  • Data-quality engine with quarantine and abort thresholds, schema-drift contracts, ANSI-safe parsing of every register's quirks.
  • Tiered geocoding with offline joins and free government geocoders, instead of a paid API.
  • Change detection: an unchanged month costs one small task. CI/CD with tests, approval and service-principal deploys.
  • Results published as static JSON: a live map and insights on operating companies, fishing hubs and company survival.

What I'm working on

  • Shipped A lakehouse that cleans, historises and geocodes six European company registers every month on Databricks serverless and AWS, with a live map of the results.
  • Certified AWS Certified Cloud Practitioner, earned in October 2026. In production in my lakehouse: Lambda, S3, IAM, EventBridge, CloudWatch and SAM.
  • Writing Question-by-question study guides on AWS, PySpark, Python, PostgreSQL and dbt.

Skills & tools

Languages
  • Python
  • SQL
  • Scala
Big Data
  • Apache Spark
  • PySpark
  • Hadoop
  • Hive
  • Apache NiFi
Cloud & lakehouse
  • Databricks
  • Delta Lake
  • AWS
  • Google BigQuery
  • Azure Data Factory
Data modelling
  • Data Vault 2.0
  • Medallion architecture
  • Dimensional modelling
  • PostgreSQL
Orchestration
  • Apache Airflow
  • Control-M
  • Azure Data Factory
  • AWS Lambda
Quality & DevOps
  • pytest
  • ScalaTest
  • Docker
  • Git
  • GitLab

Let's talk data

Hiring for a data engineering role, or want to discuss a pipeline? I would be glad to hear from you.

Get in touch