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- Tasks: Design and implement scalable, real-time data processing systems using Kafka.
- Company: Join a dynamic team focused on innovative data solutions in a fast-paced environment.
- Benefits: Enjoy flexible working options, competitive pay, and opportunities for professional growth.
- Why this job: Be at the forefront of technology, shaping real-time data processing and making a significant impact.
- Qualifications: Extensive experience with Apache Kafka and real-time architecture is essential.
- Other info: Stay updated with the latest industry practices and collaborate with cross-functional teams.
The predicted salary is between 48000 - 72000 £ per year.
A Kafka Real-Time Architect is responsible for designing and implementing scalable, real-time data processing systems in Kafka. This role involves architecting Kafka clusters, ensuring high availability, and integrating with other data processing tools and platforms.
- Designing and architecting scalable, real-time systems in Kafka.
- Configuring, deploying, and maintaining Kafka clusters to ensure high availability and scalability.
- Integrating Kafka with other data processing tools and platforms such as Kafka Streams, Kafka Connect, Spark Streaming, Schema Registry, Flink, and Beam.
- Collaborating with cross-functional teams to understand data requirements and design solutions that meet business needs.
- Implementing security measures to protect Kafka clusters and data streams.
- Monitoring Kafka performance and troubleshooting issues to ensure optimal performance.
- Providing technical guidance and support to development operations teams.
- Staying updated with the latest Kafka features, updates, and industry practices.
Required Skills Experience:
- Extensive experience with Apache Kafka and real-time architecture including event-driven frameworks.
- Strong knowledge of Kafka Streams, Kafka Connect, Spark Streaming, Schema Registry, Flink, and Beam.
- Experience with cloud platforms such as GCP Pub/Sub.
- Excellent problem-solving skills.
Knowledge & Experience / Qualifications:
- Knowledge of Kafka data pipelines and messaging solutions to support critical business operations and enable real-time data processing.
- Monitoring Kafka performance, enhancing decision making and operational efficiency.
- Collaborating with development teams to integrate Kafka applications and services.
- Maintain an architectural library for Kafka deployment models and patterns.
- Helping developers to maintain Kafka connectors such as JDBC, MongoDB, and S3 connectors, along with topics schemas, to streamline data ingestion from databases, NoSQL data stores, and cloud storage, enabling faster data insight.
Kafka Architect employer: JR United Kingdom
Contact Detail:
JR United Kingdom Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Kafka Architect
✨Tip Number 1
Familiarise yourself with the latest features and updates in Apache Kafka. Being well-versed in the most recent advancements will not only boost your confidence during interviews but also demonstrate your commitment to staying current in the field.
✨Tip Number 2
Engage with the Kafka community through forums, webinars, and meetups. Networking with other professionals can provide valuable insights and may even lead to referrals for job openings at companies like us.
✨Tip Number 3
Prepare to discuss real-world scenarios where you've implemented Kafka solutions. Be ready to explain your thought process and the impact of your work on business operations, as this will showcase your practical experience.
✨Tip Number 4
Brush up on your collaboration skills, as this role requires working closely with cross-functional teams. Highlight any past experiences where you successfully collaborated on projects, as this will be crucial in demonstrating your fit for our team.
We think you need these skills to ace Kafka Architect
Some tips for your application 🫡
Understand the Role: Before applying, make sure you fully understand the responsibilities of a Kafka Architect. Familiarise yourself with the key skills and technologies mentioned in the job description, such as Apache Kafka, Kafka Streams, and cloud platforms like GCP.
Tailor Your CV: Customise your CV to highlight your experience with Kafka and real-time data processing systems. Include specific projects or roles where you've implemented Kafka solutions, and emphasise your problem-solving skills and collaboration with cross-functional teams.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for real-time data architecture and your expertise in Kafka. Mention how your background aligns with the company's needs and how you can contribute to their data processing goals.
Showcase Relevant Projects: If applicable, include links to any relevant projects or contributions you've made in the Kafka ecosystem. This could be GitHub repositories, articles, or case studies that demonstrate your technical skills and understanding of Kafka's capabilities.
How to prepare for a job interview at JR United Kingdom
✨Showcase Your Kafka Expertise
Make sure to highlight your extensive experience with Apache Kafka and real-time architecture. Be prepared to discuss specific projects where you've designed and implemented scalable systems, as well as any challenges you faced and how you overcame them.
✨Demonstrate Integration Skills
Since the role involves integrating Kafka with various tools like Kafka Streams and Spark Streaming, be ready to explain your experience with these technologies. Discuss how you've collaborated with cross-functional teams to meet data requirements and design effective solutions.
✨Emphasise Problem-Solving Abilities
Employers are looking for strong problem-solving skills. Prepare examples of how you've monitored Kafka performance, troubleshot issues, and optimised systems. This will show that you can maintain high availability and scalability in real-time data processing.
✨Stay Updated on Industry Practices
Being knowledgeable about the latest Kafka features and industry practices is crucial. Mention any recent updates or trends you've followed, and how you plan to implement new features or improvements in your work. This shows your commitment to continuous learning.
