Data Engineer
ASP Group · Berlin
Skills in this posting
Benefits
The posting
AI Service Partners (ASP) helps enterprise clients successfully implement and scale GenAI and data initiatives, from central data platforms to intelligent automation, working out of Munich and Berlin. We work close to the client, solving real operational problems rather than building demos, and we're building a team that combines technical depth with a pragmatic, ownership-driven delivery mindset.
As Data Engineer at ASP, you'll build the technical backbone behind our clients' data and AI initiatives: designing pipelines, integrations, and data infrastructure that run in real corporate production environments, not sandboxes. You'll work directly on high-stakes enterprise projects where your work is the foundation everything else, from reporting to automation to GenAI use cases, is built on.
Tasks
Design, build, and operate data pipelines, integrations, and data infrastructure in real corporate production environments
Build APIs and connectors to integrate heterogeneous systems and keep data mapped consistently across them
Set up and manage cloud data infrastructure, including access rights, identity, and security configuration
Work with modern data platform tools such as Microsoft Fabric, Databricks, or similar to build and operate scalable data solutions for clients
Lay the technical foundation that everything else, from reporting to automation to GenAI use cases, is built on
Requirements
Experience designing, building, and operating data pipelines in a corporate production environment
A solid understanding of data quality practices and how to map data consistently across systems
Hands-on experience integrating heterogeneous systems, including building APIs and connectors
Knowledge of one or more cloud providers (e.g., Microsoft Azure), including setting up access rights/IAM and security configuration
Experience with modern data platform tools such as Microsoft Fabric, Databricks, or similar
Good knowledge of networking and security fundamentals as they apply to data infrastructure
A proven track record delivering this kind of work, ideally on real, high-stakes projects rather than internal or academic ones, is a big plus
Benefits
We're a young company with strong growth ahead of us over the next few years, and we want the people who join early to grow with us, both in role and in responsibility. Compensation includes a competitive base salary that scales with your experience in the role, equity, and a performance-based bonus, so your success is directly tied to the company's.
We don't believe in a "perfect" candidate. Apply even if you don't check every box. Skills and experience are valued over formal degrees, motivation and drive matter as much as your CV, and we favor ownership over hierarchy: everyone is expected to drive outcomes, not wait for instructions. We have a bias toward action and give and expect direct, honest feedback.
If this sounds like you, we'd love to hear from you!
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The PivotHop read
- What a data engineer actually earnsmedian, seniority, by country
- Careers a data engineer can move intoevery measured route out
- Data Architect → Data Engineer47% readiness
- Data Analyst → Data Engineer30% readiness
- All open data engineer rolesthe full board
Where these skills also reach
- 97 open data architect roles85% readiness from data engineer
- 600 open solutions architect roles62% readiness from data engineer
- 600 open data analyst roles57% readiness from data engineer
- 71 open database administrator roles57% readiness from data engineer
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