Senior: Cyber Defense Engineering - Data Management

Madrid, España

Deloitte

Für unsere Kunden entwickeln wir integrierte Lösungen. Unsere Services umfassen Wirtschaftsprüfung, Steuerberatung, Financial Advisory und Consulting.

View company page

 

 

 

To join Deloitte is to participate in the transformation of leading national and international organisations. At Deloitte we are committed to making an impact on society, our clients and you.

 

Are you in?

 

 

As a part of the team, you will provide ongoing engineering of the current Splunk infrastructure as well as the migration/implementation of Splunk products in a global multi-data center environment. This role also requires a forward-thinking consultative approach and a high degree of collaboration with the Splunk architecture and Infrastructure teams.

 

 

What will your day-to-day be like?

 

  • Develop requirements for data ingestion methods based on input from stakeholders/leadership.
  • Clearly document and diagram deployment-specific aspects of architectures and environments, working closely with various teams to create application runbooks, playbooks, and knowledge base documents.
  • Troubleshoot issues in production and other environments, applying debugging and problem-solving techniques (e.g., log analysis, non-invasive tests).
  • Suggest deployment patterns & practices improvements based on learnings from past deployments and production issues, collaborate with GEMS Engineering team members to implement these.
  • After hours on-call support occasionally required.


 

What do we expect from you?
 

  • Bachelor’s degree: preferably in an information technology-related field of study, or equivalent years of experience required.
  • Minimum of 2 years of Splunk engineering experience.
  • Strong understanding of Cloud Services – Azure, AWS.
  • Strong understanding of Splunk data onboarding including Splunk App/TA configuration and CIM validation.
  • Universal/Heavy Forwarder configuration experience, including encryption and compression settings.
  • Experience working with a strict change control process utilizing tools such as Azure DevOps.
  • Management/deployment experience with large scale/distributed Splunk environments.
  • A solid understanding of Windows and Linux administration utilizing Command Line Interface (CLI).
  • Knowledge of networking, firewalls, load balancers etc.
  • Demonstrate understanding of common enterprise applications (especially in the area of security).
  • Knowledge of best practices for IT operations in an always-on, always-available service model.
  • Preferred: experience with Cribl administration and data onboarding.
  • Preferred: Splunk Certified Admin.

 

 

What do we offer?

 

  • You will have a hybrid-flexible working model.
  • You will be eligible for a flexible remuneration system, medical service, health insurance, life insurance and accident insurance.
  • You will have a training plan throughout your career.
  • You will develop in a feedback culture where you will be encouraged to learn continuously.
  • If you are interested, you will participate in national and international social action and volunteering programmes.
  • You will enjoy a cultural and sporting offer.

 

 

Now the choice is yours! If you think this position is right for you, click 'Apply now' and complete your profile so we can assess your application. If you fit the profile, our recruitment team will contact you to get to know you.

From there we will guide you through our recruitment process and your Deloitte story will begin.

 

 

What impact will you make?

 

Apply now Apply later
  • Share this job via
  • or

* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

Tags: Architecture AWS Azure Data management DevOps Engineering Linux Security Splunk

Perks/benefits: Flex hours

Region: Europe
Country: Spain
Job stats:  3  0  0
Category: Engineering Jobs

More jobs like this

Explore more AI, ML, Data Science career opportunities

Find even more open roles in Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Computer Vision (CV), Data Engineering, Data Analytics, Big Data, and Data Science in general - ordered by popularity of job title or skills, toolset and products used - below.