Data Engineer at ASP Group

Berlin, Berlin, Germany -

Full Time

Start Date

Immediate

Expiry Date

21 Dec, 26

Salary

50000.0

Posted On

22 Sep, 26

Experience

4 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Yes

Skills

Industry

Information Technology & Services

Description

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

How To Apply:

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Responsibilities

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

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