Data Engineer Trainee

About the role

Budapest, hybrid

DEPT® is a Growth Invention company built to help the world’s most ambitious brands grow faster. Operating at the intersection of technology and marketing, our 4,000+ specialists deliver growth invention services across Brand & Media, Experience, Commerce, CRM, and Technology & Data. We’re 50|50 tech and marketing, partner-led, and first to move. Clients include Google, Lufthansa, Meta, eBay, and OpenAI. We have been certified B Corp and Climate Neutral since 2021.

ABOUT THE TRAINEESHIP

The Data Engineering Traineeship is a four-month, on-the-job program You join our Data Engineering team on day one and work on real client projects within your first weeks. Three things shape your four months:

- Real client work from the start. You'll contribute to live projects for brands such as Philips, Foot Locker, Nikon and Rituals, taking on more ownership each month. By month four you'll be working much like a junior data engineer.

- Masterclasses. A light, applied curriculum run by our engineers. Practical sessions on the tools and patterns we use with clients, not a repeat of university theory.

- A named buddy. A senior engineer who plans your week with you, reviews your work and is accountable for your progress.

ABOUT THE ROLE

You'll join the Data Engineering team in our EMEA Data & AI craft, working from Budapest, where our lead and senior data engineer are based. We design and build scalable, reliable data platforms and pipelines for enterprise clients across Europe, and work closely with our analytics, data science and AI teams on integrated solutions. You'll write real code that runs in client environments, with experienced engineers reviewing it and helping you grow.

WHAT YOU'LL DO

- Build and maintain data pipelines that ingest, transform and model client data, with guidance from senior engineers

- Write clean, tested SQL and Python

- Develop data models in cloud data warehouses such as BigQuery or Snowflake, using tools like dbt

- Help orchestrate and monitor workflows with tools such as Airflow

- Add data quality checks, tests and documentation so that others can trust and reuse your work

- Work in a team setup with Git, code reviews and CI/CD

- Explain what you've built to colleagues and clients

WHAT YOU BRING

- A degree in computer science, data science, engineering, mathematics or a related field, or you'll complete one before February 2027

- Some work experience in data, software or analytics engineering: a student job, an internship or up to around one year full-time

- Good SQL and working Python

- An understanding of data modeling basics and ETL/ELT concepts

- Exposure to at least one cloud platform (GCP, AWS or Azure), from work, coursework or your own projects

- Familiarity with Git

- Clear written and spoken English, and the ability to explain technical work in plain language