Your area of work:
In your new position, you will become a member of the Cyber Defense team, which is part of the department of Group Security. The Cyber Defense team is responsible for all aspects of Security Information and Event Management (SIEM), Computer Emergency Response (CERT), and Security Operations Center (SOC). In order to fully protect the information assets of DBG, Cyber Defense is aiming to achieve a proactive detection of threats and improve monitoring of DBG information assets to protect them from cyber-attacks effectively, dealing with implementation and maintenance a state-of-the-art SIEM/SOC tooling, architecture and use cases content in order to support establishing Cyber Defense as a center of excellence for threat intelligence.
Your focus will be on building robust, performant and compliant processes to extract, model and serve security-related data to the ML-based cyber security models. You will be transforming existing ML-powered case prototypes into production-grade processes. Besides that, you will support various Information Security related projects ensuring robustness and the state-of-the-art solutions following the regulatory requirements and the best industry practices.
Your responsibilities:
1. Scale up and transform existing ML-powered use case prototypes into production-grade processes.
2. Design and optimize data models supporting machine learning-based cyber security use cases.
3. Design and deploy production-grade ETL/ELT pipelines (batch / streaming).
4. Use corporate blueprints (Terraform) to build compliant, robust and performant processes.
5. Contribute to the development and optimization of machine learning models.
Your profile:
6. University or comparable degree in Computer Science, Information Security, Engineering or related discipline.
7. Interest in cyber security related topics.
8. 3+ years of experience in data engineering.
9. Solid technical background and practical knowledge of modern data engineering tools (e.g. SQL, trino, MinIO, dbt, Kafka, Spark, databricks, REST API).
10. Experience with cloud platforms (e.g. GCP, Azure).
11. Practical understanding of machine learning requirements on data and the underlying processes.
12. Experience with one or more of the following languages Python/Go/Java.
13. Experience with automation and orchestration technologies (most relevant being: Terraform, Docker, Kubernetes).
14. Be able to take responsibility and deliver results autonomously, sometimes under time pressure.
Why Deutsche Börse Group?
We are committed to providing a work environment where everyone feels welcome and can reach their full potential. Our standards go far beyond simply matching candidates with the right position.
Mobility
We enable you to move freely with our job tickets, job (e-)bikes and free parking opportunities.
Work environment
Collaboration, communication, or deep focus – in our modern office buildings you will find the perfect work environment. Free drinks and food and meal allowances included.
Health and wellbeing
We care for your health and wellbeing and besides various health promotion measures we offer you a group accident insurance and additional insurance offers at discounted rates.
Financial stability
We provide financial stability by offering attractive salaries, company pension schemes, participation in our Group Share Plan, as well as bonuses, subsidies and discounts.
Hybrid work
Collaborate and exchange on-site or work remotely several days a week in line with business needs and local regulations. Our hybrid working model combines the best of both worlds.
Flexible working hours
We want your job to fit your life situation and offer flexible working time models, childcare allowance, or the possibility to study alongside your job.
Internationality
Our market infrastructures are globally connected. Working with us means collaborating with like-minded colleagues across over 60 locations from more than 100 nations.
Development
We promote individual development by offering internal development programmes, mentoring, further education and training budgets.