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Data Engineer (m/f/d)

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Onsite

Data Engineer (m/f/d)

Rheinmetall

Data Engineer (m/f/d)

Skills

SQL QueriesData EngineeringPythonDevOpsKafkaCybersecurityMachine LearningAILinuxKubernetes

17 days ago

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Important information


Contract type:

Permanent

Location:

28 Bremen, Germany

Work mode:

Onsite

Published on:

3 October 2026

What they need


What We Are Looking For

  • Design, further development, and practical implementation of a scalable data lakehouse and data platform architecture for very large, heterogeneous data sets
  • Developing a long-term data and storage strategy that takes into account performance, scalability, data lifecycle, costs, availability, and operational requirements
  • Designing suitable storage and access concepts for large volumes of image, video, sensor, geospatial, and other unstructured and semi-structured data, including metadata, partitioning, indexing, compression, and archiving
  • Building and operating robust batch and streaming pipelines for the ingestion, processing, transformation, and delivery of data from heterogeneous sources
  • Co-design and implementation of a semantic data model or ontology that enables data objects, entities, relationships, and context to be described and linked across systems
  • Creating a resilient data foundation for machine learning, AI-based applications, and autonomous systems, including traceable data provenance and reproducible training and validation datasets
  • Ensuring data lineage, data versioning, data quality, schema management, and appropriate governance and access concepts throughout the entire data lifecycle
  • Development and operation of the data platform in large, distributed Kubernetes-based infrastructures, as well as integration into Infrastructure-as-Code and CI/CD/DevSecOps processes
  • Analyzing and optimizing data layouts, data locality, compute proximity, and data movements for data-intensive applications
  • Evaluation of suitable open-source and commercial technologies, as well as implementation ranging from proofs of concept to production-ready, scalable solutions
  • Close collaboration with AI/ML, software, platform, and cybersecurity teams on architectural decisions, interfaces, data products, and operational implementation

What Qualifications You Should Have

  • A degree in computer science, data engineering, software engineering, business informatics, or a comparable practical qualification
  • Several years of hands-on experience in data engineering and in building or further developing distributed data platforms
  • A very good understanding of modern data lake/lakehouse architectures, object storage, and the fundamental trade-offs between storage, compute, data movement, performance, and costs
  • Demonstrable hands-on experience with data pipelines, data modeling, SQL, and at least one relevant programming language, preferably Python
  • Solid knowledge of metadata, data quality, schema management, data lineage, and reproducible processing
  • Practical understanding of Linux, containers, and Kubernetes, as well as the ability to independently implement, operate, and analyze data components in a distributed platform
  • Ability to link architectural decisions to practical implementation and to systematically investigate problems down to their technical root causes
  • A structured, team-oriented approach to work, as well as strong written and spoken English skills
  • Experience with very large volumes of image, video, sensor, or geodata
  • Knowledge of ontologies, knowledge graphs, semantic data models, entity resolution, or comparable approaches
  • Experience with technologies for distributed data processing and streaming, e.g., Spark, Flink, Trino, Kafka, or comparable solutions
  • Experience with open Lakehouse table formats or comparable technologies, such as Apache Iceberg, Delta Lake, or Apache Hudi
  • Experience in provisioning and versioning data for machine learning, MLOps, AI, or autonomy workloads
  • Knowledge of Infrastructure as Code, GitOps, or automated platform and deployment processes
  • Experience with highly available, on-premises, edge, or intermittently disconnected data platforms

A solid foundation and practical implementation experience are crucial for this role. Additional specialized knowledge is expressly not a requirement. Stärken und Erfahrungen zählen bei Rheinmetall, auch wenn vielleicht nicht alle aufgeführten Anforderungen vollständig erfüllt sind. Wir freuen uns auf Bewerber (m/w/d), die Lust haben, etwas zu bewegen und Verantwortung zu übernehmen. Wir legen Wert auf Individualität und Chancengleichheit. Schwerbehinderte Bewerber (m/w/d) werden bei gleicher Eignung besonders berücksichtigt.

What We Offer You At our location in Bremen, we offer you:

  • Company pension scheme
  • Share purchase programme
  • 30 days of holiday
  • Access to corporate benefits
  • Deutschlandticket
  • Relocation support
  • Mobile working
  • VIVA family service
  • Individual and diverse internal and external development opportunities, including at the Rheinmetall Academy
  • Professional induction process supported by digital onboarding

CONTACT INFORMATION

Contact Person: Ms Özge Demirkaya

For questions regarding your application, please use the contact form.

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