How do I apply for the Working Student Data Engineer - Data & Platform Engineering (all genders) position at HeyJobs and track my application?

We provide a direct link to the official application portal. You can apply directly here . Additionally, you can easily track this and other applications by clicking the bookmark icon to save it to your YGI Kanban board .

Is the internship at HeyJobs paid and what compensation can candidates expect?

Yes, this is a paid internship opportunity. Exact compensation details are typically finalized during the company interview process.

What are the working arrangements and expected duration for the Working Student Data Engineer - Data & Platform Engineering (all genders) role?

This position is a part-time, structured as a hybrid role, with an expected duration of 12 months.

What educational background or degree level is required for the Working Student Data Engineer - Data & Platform Engineering (all genders) at HeyJobs?

Candidates are generally expected to be holding or pursuing the following degree levels: Bachelor, Master.

Does HeyJobs provide visa sponsorship or assistance for international applicants?

Regarding visa assistance and sponsorship for this role, the official status is currently listed as: Not disclosed.

Working Student Data Engineer - Data & Platform Engineering (all genders)

HeyJobs

Found 1 month ago

Location

Berlin, Germany

Duration (Months)

12 Months

Time

Part-time

Work Mode

Hybrid

Salary

16 - 18 €/hourly

Visa Help

Not disclosed

Last Verified

1 month ago

Education

Bachelor
Master

Skills & Qualifications

Technical Skills

SQL
AWS
GenAI
data warehousing
architecture
tooling
governance
Docker
container platforms
ECS
infrastructure-as-code tools
Terraform
CloudFormation

Soft Skills

general software development
problem-solving mindset
Agile ways of working
communication skills

Job Description

Support a broad range of operational initiatives, including: Hands-on data operations (onboarding/offboarding, helpdesk tickets, bug fixes) Low–medium complexity data engineering and platform work, leveraging GenAI Identifying and implementing end-to-end automation opportunities using GenAI Supporting team rituals, planning, and stakeholder management Organising workload and communicating priorities and challenges Maintaining clear, accessible documentation and playbooks for technical and non-technical audiences Translating technical concepts into business-friendly insights and facilitating cross-functional alignment Act as a Product Engineer: Own problems end to end - from identifying the right opportunity to delivering and maintaining production data products - combining product thinking with engineering execution and AI acceleration.

Requirements

Active enrollment at a German university in Computer Science, Engineering, or a related field.
Ideally graduating in 2027 or early 2028, with interest in converting to full-time (long-term collaboration)
Working knowledge of SQL and general software development
Experience with AWS or other cloud providers
Strong interest in data and data platform engineering (e.g. data warehousing, architecture, AWS, tooling, governance)
Motivation to grow into a Product Engineer for Data & Platform Engineering
Availability to work 3–4 days per week on an ongoing basis
Proactive, fast learner with a problem-solving mindset
Familiarity with Agile ways of working and tools like Jira, Confluence, and GitHub
Strong, clear communication skills in English

Data & Analytics

Data Engineering

Languages

English

Nice to Haves

Prior experience in software, infrastructure, or technical product/project roles
Experience with Docker and container platforms (e.g. ECS)
Exposure to infrastructure-as-code tools (Terraform, CloudFormation)
Experience in vendor management or contract negotiations

Apply Now

19Open Positions

Open Positions

19Open Positions

Working Student Data Engineer - Data & Platform Engineering (all genders)

Education

Skills & Qualifications

Technical Skills

Soft Skills

Job Description

Requirements

Related Field

Related Subfield

Languages

Nice to Haves