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Data Engineer Intern - BDAA Big Data - TalentBank 2026

Summary

Data Engineer Intern builds and maintains cloud-based ETL pipelines and data pipelines in Google Cloud to feed Commerzbank’s Big Data cluster, ensuring data quality and integrity for analytics and data science teams.

TalentBank is an original internship program of the Digital Technology Centre in Poland, which aims to enable students and graduates to gain professional experience in IT and banking industry. The project can be attended by people who are students or graduates (up to 12 months after graduation). We look for students after second year of technical, mathematical, business, finance, economic or related studies.

Join our team as a Data Engineer Intern!

In your role as a Data Engineer you will be working in the Big Data Cluster, which is the enabler for data scientists and provides a huge collection of data and a data science workbench in one place.

On a daily basis you will develop products based on database technology which are running in the On‑Premise or Cloud. Your responsibilities will encompass the full Software Development Lifecycle including analysis, architecture, testing and also supporting during production issues during normal working hours.

What you will be doing?

  • Setting up data pipelines / ETL processes on cloud platforms (in particular Google Cloud)
  • Ensuring data quality and integrity throughout the data lifecycle.
  • Focusing on stability, performance tuning and innovation of the applications/ monitoring
  • Talking to sources about their source systems technologies and how to retrieve the data in an efficient way (file formats like csv, XML, JSON)
  • Designing data structures (e.g. table partitioning, data formats)
  • Exchange with the data platform team to give feedback and improvement ideas
  • Taking care of proper up-to-date documentation of data and metadata
  • Actively contributing to knowledge sharing and to a learning culture
  • Working in the international projects in agile methodologies.

Which technology & skills are important for us?

  • Good knowledge of SQL
  • Good knowledge of Python and Cloud

What we offer?

  • Paid mandate contract for 9 months
  • Opportunity to gain experience and start career in our IT departments
  • Work in an international environment in the Agile methodology
  • Individual approach - flexible working hours, the possibility of combining internship with studies, completing obligatory student internships
  • Subsidized meals - Pluxee Lunch Pass card
  • Access to the Speexx e‑learning language platform
  • Access to O’Reilly and Clix (Linkedin Learning) e‑learning platform
  • Access to psychological and well‑being webinars on ICAS
  • Internal training program Skills@work (coffee Learning Session – informal quarterly meetings among employees focusing on a given technological or business issue, Trainer Academy – Technical training organized by employees for employees, Guilds – groups focusing on a given technology)
  • Support of experienced mentors
  • Trainings with Professionals
  • Interest groups (f.e. board games, cooking) and integration events

How? Hybrid on Wersalska 6 (Łódź)

Important! Please add the clause to your CV. You can find it at the end of the advert.

Below you can find more information about Commerzbank and the cluster

Commerzbank is a leading international commercial bank with branches and offices in almost 50 countries. The world is changing, becoming digital, and so we are. We are leaving the traditional bank behind us and are choosing to move forward as a digital enterprise. This is exactly why we need talented people who will join us on this journey. We work in inter-locational and international teamwork in agile methodologies.

The Big Data cluster is the enabler for data scientists and provides a huge collection of data and a data science workbench in one place.

BI technology within the lake infrastructure

Establish a stable, state‑of‑the‑art technology base with on‑prem and cloud solutions

Set up data lake as single data and analytics hub and effectively ingest most important data sources

Establish data quality and metadata management

Provide Data Marts and sandboxes for segments and functions with the most important combination of data sources

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