Senior Data Engineer (Python, ELK)

2 months ago
Full time role
In-person · Barcelona, CT, ES... more

In a nutshell

As a Senior Data Engineer you will leading our team, as you take ownership of complex tasks and guide the execution of engineering activities. You will be monitoring requirements elicitation, maintaining the team’s backlog, contributing to Architectural Decision Records (ADRs), conducting feasibility studies and proof of concepts.

You will also collaborate with the Security department on developed and delivered solutions. This position will report directly to the Program Leader. 

Where will you be based and what business will you support?

Based in Barcelona, you will join our Eurofins globally distributed IT Application Monitoring and Observability team;  which provides knowledge on operation of IT Systems and IT Infrastructure. Over 62K+ Eurofins employees relies on services that we are providing to conduct their daily operation. From basic application availability monitoring, through complex process analysis ending on advanced statistical and ML/AI methods to proactively counteract any unexpected events that can negatively impact the bussies. Handling over 3TB of data daily our goals is to collect, process, and visualize data to provide knowledge in easy and understandable way to the end users.

How can you help us? 

You will:

  • Work on monitoring requirements elicitation and maintain the team’s backlog; 
  • Contribute  to Architectural Decision Records (ADRs); 
  • Conducting feasibility studies and proof of concepts; 
  • Work extensively with Machine Learning algorithms for time series analysis (anomaly detection, pattern recognition, correlation and casual reasoning); 
  • Work with NO-SQL databases, specifically Elasticsearch with LogStash; 
  • Work with Python for data scientific purposes and REST microservice development;
  • Develop scripting skills in Bash;
  • Apply your statistical and data science concepts; 
  • Apply DevOps principles in deploying, monitoring, and operating containerized applications using Docker, Kubernetes, GitOps, and CI/CD; 
  • Resort to modelling languages such as C4, UML, and ArchiMate.
  • Utilize data visualization and storytelling techniques to convey insights effectively.