Deporvillage is one of the biggest European e-commerce companies that is a market leader in its sector.

We are handling millions of page views and thousands of orders per day. For this reason, we have to be smart with data and build the best recommendation systems for our customers.

If you want to be part of a team which is using dynamic methodologies, with cutting edge technologies and a collaborative sense, then this job is made for you

At Deporvillage, You Will

Implement data pipelines and complex DAGs to evolve and maintain our Data Lake and Data Warehouse.

Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS ‘big data’ technologies.

Use Agile methodologies oriented towards quarter OKRs.

Work closely with our data team formed by: Data Analyst and Data Scientist.

What we expect you to bring

+4 years of experience as a Data Engineer, specially in an e-commerce industry

Experience with the AWS ecosystem. Desired technologies such as: Glue Step functions, SNS, SQS are appropriate





Experience with database engines such as MySQL, MongoDB or Postgres

Experience developing ETL/ELT processes

Strong knowledge of Python

Ability to write advanced and optimal queries in SQL

Strong knowledge of data structures

Having experience in Big Data technologies such as Spark or Snowflake

Using infrastructure-as-code solutions (Terraform).

Empathy, being a team player and proactivity is a must

Nice to have:

Stream processing

AI Engineer fundamentals such as: Ability to support and implement basic AI workflows, such as connecting data pipelines to LLM endpoints and tracking model performance.

What We Offer

A young and dynamic working environment

Competitive salary based on experience

Working location flexibility (only 1 day at the office per week, even post-pandemic)

Flat hierarchy and open communication

Versátil working hours

Tax-free benefits (ticket restaurant, ki

📌 Senior Data Engineer (Madrid)
🏢 Deporvillage
📍 Madrid