Data Engineer - Knowledge Graph (m/f/d)

REFERENCE NUMBER:

640579/1

MY DUTIES:

- Consulting the data scientists in the development of algorithms and machine learning models es-pecially regarding productionization of these models Implementation of data pipelines for stream and batch processing that generate triples to feed our knowledge graph and that train and build our machine learning models
- Design and implementation of microservices that provide REST and SPARQL APIs to query the knowledge graph, including tracing and monitoring
- Deployment of the microservices in the productive cloud environment, considering scalability and high availability requirements
- Implementation of CI/CD pipelines to deploy data pipelines and microservices to production

MY QUALIFICATIONS:

- Knowledge of Google Cloud Platform, Terraform, GitLab
- Knowledge of GKubernetes, Docker, GitLab CI/CD, ArgoCD, Dataflow, Apache Beam
- Knowledge of GBigQuery, BigTable
- Knowledge of GPython, SQL, Java
- Knowledge of GREST API, GraphQL

MY BENEFITS:

- Option to work remote

ABOUT HAYS:

IT is and always has been our core business that laid the foundation for Hays' success. We are the biggest privately owned IT recruitment agency in Germany and offer the best jobs for every career level – whether you are interested in vacancies in agile SMEs or international DAX groups. Hays masters the entire IT job spectrum, from support to software architecture or digitalisation – thanks to our broad portfolio, we have something for everyone. In the last decades, we were able to support numerous IT experts with choosing the right path for a successful career, positioning ourselves as their lifelong partner. Our highly specialised consultants can cater to your every wish and expectation and will prepare you for interviews and contract negotiations. Give it a try and learn what the market has to offer – our services are free of charge, non-binding and discreet! We look forward to hearing from you.

MY CONTACT AT HAYS:

My contact person
Kristine Hergert

Reference number
640579/1

Contact
E-Mail: [email protected]
Phone: +49-(0)201-76026350