We build scalable data solutions for our (internal) customers with a strong focus on self-service and automation. Our goal is to enable customers to create and extend their own use cases through standardized data onboarding and reusable solution builing blocks.
Activity description and concrete tasks:
- Design and build data science solutions for (internal) customer use cases
- Work customer-facing: understand business problems, translate them into technical solutions and present results
- Develop scalable and reusable solution architectures instead of one-off prototypes
- Build and maintain data pipelines and onboarding processes for new data sources
- Extend self service which we offer to our internal customer (focus on automation)
- Development of Gitlab pipelines for testing and automating processes
- Collaborate with other groups (internal customer, SMOPS operation, security, connectivity)
Qualifications
- Background in Data Science/ ML/ Advanced Analytics
- Experience with NoSQL-Database
- Experience with REST-API, or JSON-Datastructures
- Enhanced Developerknowledge in Python
- Gitlab and CI/CD
- Kubernetes and Docker Deployments
- Linux
- Bash
- Cloud Computing
Additional Information
What do we offer you?
- International, positive, dynamic and motivated work environment.
- Hybrid work model (teleworking/on-site).
- Flexible schedule.
- Continuous training: Preparation for certifications, access to Coursera, weekly English and German classes...
- Flexible compensation plan: health insurance, meal vouchers, childcare, transport assistance...
- Life and accident insurance.
- More than 26 working days of vacation per year.
- Social fund.
- Free service for specialists (doctors, physiotherapists, nutritionists, psychologists, lawyers...)
- 100% of salary in case of sick leave.
And many more advantages of being part of T-Systems!
If you are looking for a new challenge, do not hesitate to send us your CV. Join our team!
T-Systems Iberia will only process the CVs of candidates who meet the requirements specified for each offer.