At a Glance
- Tasks: Design and optimise secure, enterprise-scale Elastic Stack environments.
- Company: Join a leading Defence and National Security organisation.
- Benefits: Competitive salary, flexible work options, and professional development opportunities.
- Other info: Must be a British citizen and willing to undergo DV security clearance.
- Why this job: Make a real impact in a critical sector while working with cutting-edge technology.
- Qualifications: Proven experience with Elastic Stack and strong technical skills.
Great opportunity for an experienced Elastic SME to design, implement, optimise and support a secure, enterprise-scale on-premises Elastic Stack environment. The role is working in a Defence and National Security environment; as such, you MUST be willing and able to undertake DV security clearance (you must be a British citizen and have lived in the UK for the last 10 years).
You’ll take technical ownership of the Elastic platform, supporting Elasticsearch, Kibana, Logstash, Beats, Elastic Agent, Fleet, Elastic Security (SIEM) and Elastic Observability across a complex enterprise estate.
Key responsibilities:
- Design and support resilient, highly available on-premises Elastic Stack environments
- Administer and optimise large-scale Elasticsearch clusters
- Deliver Elastic Security (SIEM) and Elastic Observability solutions
- Build ingestion pipelines using Logstash, Elastic Agent and Beats
- Configure Kibana dashboards, visualisations, RBAC and reporting
- Implement TLS, PKI, LDAP/Active Directory, SAML and platform hardening
- Optimise cluster performance, JVM, shards, ILM and storage
- Automate deployments and operational tasks using PowerShell, REST APIs, Python and/or Ansible
- Provide 3rd/4th line support, troubleshooting and RCA
- Produce HLDs, LLDs, SOPs, runbooks and DR documentation
Essential experience:
- Enterprise on-premises Elastic Stack experience
- Strong Elasticsearch, Kibana and Logstash experience
- Strong Elastic Agent, Beats and Fleet experience
- Strong Elastic Security (SIEM) and Elastic Observability experience
- Experience managing large, highly available Elasticsearch clusters
- Splunk experience
- Strong automation experience
You must have proven experience administering enterprise on-premises Elastic Stack environments, including Elasticsearch clusters, Elastic Security (SIEM) and Elastic Observability. This role particularly suits an Elastic SME / Elastic Stack Engineer with extensive Elasticsearch, Kibana, Logstash, Elastic Agent, Fleet, Elastic Security and Elastic Observability experience.
Elastic SME in Hemel Hempstead employer: Fynity
Fynity is an exceptional employer, offering a dynamic work environment in Hemel Hempstead where you can contribute to vital Defence and National Intelligence systems. With a strong focus on employee growth, we provide opportunities for professional development and skill enhancement, all while fostering a collaborative culture that values innovation and teamwork. Join us to be part of a mission-driven team dedicated to tackling real-world threats, with the added advantage of working in a highly secure and supportive setting.
StudySmarter Expert Advice🤫
We think this is how you could land Elastic SME in Hemel Hempstead
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Fynity.
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We think you need these skills to ace Elastic SME in Hemel Hempstead
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Fynity, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Fynity. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Fynity
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Fynity!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
