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- Tasks: Design and maintain data pipelines for OpenShift telemetry at scale.
- Company: Join a leading tech firm focused on innovative data solutions.
- Benefits: Attractive salary, flexible working options, and growth opportunities.
- Why this job: Be at the forefront of data engineering and make a significant impact.
- Qualifications: Experience with Kafka, OpenShift, and strong Python skills required.
- Other info: Collaborative team environment with a focus on cutting-edge technology.
The predicted salary is between 48000 - 72000 £ per year.
Key Responsibilities:
- Design, implement, and maintain data pipelines to ingest and process OpenShift telemetry (metrics, logs, traces) at scale.
- Stream OpenShift telemetry via Kafka (producers, topics, schemas) and build resilient consumer services for transformation and enrichment.
- Engineer data models and routing for multi-tenant observability; ensure lineage, quality, and SLAs across the stream layer.
- Integrate processed telemetry into Splunk for visualization, dashboards, alerting, and analytics to achieve Observability Level 4 (proactive insights).
- Implement schema management (Avro/Protobuf), governance, and versioning for telemetry events.
- Build automated validation, replay, and backfill mechanisms for data reliability and recovery.
- Instrument services with OpenTelemetry; standardize tracing, metrics, and structured logging across platforms.
- Use LLMs to enhance observability capabilities (e.g., query assistance, anomaly summarization, runbook generation).
- Collaborate with platform, SRE, and application teams to integrate telemetry, alerts, and SLOs.
- Ensure security, compliance, and best practices for data pipelines and observability platforms.
- Document data flows, schemas, dashboards, and operational runbooks.
Required Skills:
- Hands-on experience building streaming data pipelines with Kafka (producers/consumers, schema registry, Kafka Connect/KSQL/KStream).
- Proficiency with OpenShift/Kubernetes telemetry (OpenTelemetry, Prometheus) and CLI tooling.
- Experience integrating telemetry into Splunk (HEC, UF, sourcetypes, CIM), building dashboards and alerting.
- Strong data engineering skills in Python (or similar) for ETL/ELT, enrichment, and validation.
- Knowledge of event schemas (Avro/Protobuf/JSON), contracts, and backward/forward compatibility.
- Familiarity with observability standards and practices; ability to drive toward Level 4 maturity (proactive monitoring, automated insights).
- Understanding of hybrid cloud and multi-cluster telemetry patterns.
- Security and compliance for data pipelines: secret management, RBAC, encryption in transit/at rest.
- Good problem-solving skills and ability to work in a collaborative team environment.
- Strong communication and documentation skills.
Data Engineer Lead (Openshift) in Sheffield employer: Infoplus Technologies UK Ltd
Contact Detail:
Infoplus Technologies UK Ltd Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer Lead (Openshift) in Sheffield
✨Tip Number 1
Network like a pro! Get out there and connect with folks in the industry. Attend meetups, webinars, or even local tech events. You never know who might have the inside scoop on job openings or can refer you directly to hiring managers.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your projects, especially those related to data pipelines and OpenShift. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice common interview questions related to data engineering and be ready to discuss your experience with Kafka, OpenTelemetry, and Splunk. Confidence is key!
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities waiting for talented individuals like you. Plus, it’s a great way to ensure your application gets seen by the right people.
We think you need these skills to ace Data Engineer Lead (Openshift) in Sheffield
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with data pipelines, Kafka, and OpenShift. We want to see how your skills match the job description, so don’t be shy about showcasing relevant projects!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about data engineering and how you can contribute to our team. Keep it concise but impactful – we love a good story!
Showcase Your Technical Skills: When filling out your application, be specific about your technical skills. Mention your hands-on experience with Python, telemetry integration, and any tools like Splunk or OpenTelemetry. We’re keen to see what you bring to the table!
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 the role. Plus, it’s super easy – just a few clicks and you’re done!
How to prepare for a job interview at Infoplus Technologies UK Ltd
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, especially Kafka, OpenShift, and Splunk. Brush up on your hands-on experience with streaming data pipelines and be ready to discuss specific projects where you've implemented these tools.
✨Showcase Your Problem-Solving Skills
Prepare to share examples of how you've tackled complex data engineering challenges. Think about situations where you had to ensure data quality or implement schema management, and be ready to explain your thought process and the outcomes.
✨Understand Observability Levels
Familiarise yourself with observability concepts, particularly Level 4 maturity. Be prepared to discuss how you’ve contributed to proactive monitoring and automated insights in previous roles, and how you can apply that knowledge to enhance the company's observability capabilities.
✨Communicate Clearly
Strong communication is key, especially when collaborating with different teams. Practice explaining technical concepts in a way that’s easy to understand, and be ready to document your thought process during the interview. This will show your potential employer that you can effectively share knowledge and work within a team.
