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- Tasks: Design and implement data pipelines for OpenShift telemetry using Kafka.
- Company: Leading technology firm in the UK with a focus on innovation.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Why this job: Join a collaborative team and drive proactive insights through data engineering.
- Qualifications: Strong Python skills and experience with observability standards required.
- Other info: Exciting role with potential for career advancement in a dynamic environment.
The predicted salary is between 43200 - 72000 £ per year.
A technology firm in the United Kingdom is looking for a data engineer to design and implement data pipelines that handle OpenShift telemetry. The role involves utilizing Kafka for data streaming, integrating telemetry into Splunk for visualization, and ensuring data quality and compliance.
Candidates should have strong skills in Python and experience with observability standards. This position offers an opportunity to work in a collaborative team environment, driving proactive insights through data engineering.
Observability Data Engineering Lead employer: Test Triangle Ltd
Contact Detail:
Test Triangle Ltd Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Observability Data Engineering Lead
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data pipelines, especially those involving OpenShift and Kafka. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on observability standards and data quality practices. Be ready to discuss how you've tackled similar challenges in the past, as this will demonstrate your expertise and problem-solving skills.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Plus, it’s a great way to ensure your application gets the attention it deserves.
We think you need these skills to ace Observability Data Engineering Lead
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your experience with Python and any relevant data engineering projects. We want to see how you've tackled challenges in the past, especially with OpenShift telemetry and Kafka!
Tailor Your Application: Don’t just send a generic CV! Customise your application to reflect the job description. Mention your familiarity with observability standards and how you can contribute to our collaborative team environment.
Be Clear and Concise: Keep your application straightforward and to the point. We appreciate clarity, so make sure your achievements and experiences are easy to read and understand. Bullet points can help!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity!
How to prepare for a job interview at Test Triangle Ltd
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, especially OpenShift, Kafka, and Splunk. Brush up on how these tools work together to handle telemetry data, as you might be asked to explain your experience with them.
✨Showcase Your Python Skills
Prepare to discuss specific projects where you've used Python for data engineering tasks. Be ready to share examples of how you’ve implemented data pipelines or ensured data quality using Python, as this will demonstrate your hands-on experience.
✨Understand Observability Standards
Familiarise yourself with observability standards and best practices. You might be asked about how you ensure compliance and data quality in your previous roles, so having concrete examples will help you stand out.
✨Emphasise Team Collaboration
Since this role involves working in a collaborative environment, think of examples that highlight your teamwork skills. Be prepared to discuss how you’ve worked with others to drive insights through data engineering, as this will show you’re a good fit for their culture.