Software Engineer - Data Infrastructure - Kafka

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Written by AI from the job title and company, not by Canonical, so some details may not match this job. The employer's own page has the real description.

Overview

As a Software Engineer specializing in Data Infrastructure at Canonical, you will play a critical role in designing, developing, and maintaining scalable data solutions utilizing Kafka technology. This position involves collaborating with cross-functional teams to ensure the architecture meets the performance and reliability standards required for our data-driven applications. You will be responsible for implementing data ingestion pipelines, optimizing data processing flows, and enhancing system performance. Your expertise will contribute significantly to advancing our data infrastructure and supporting innovative projects across the organization.

Job Responsibilities

• Design and implement scalable data pipelines leveraging Kafka.
• Collaborate with data architects and engineers to enhance data infrastructure.
• Monitor and optimize the performance of data processing systems.
• Develop and maintain documentation for data workflows and systems.
• Participate in code reviews to ensure high-quality software outputs.
• Troubleshoot and resolve issues related to data ingestion and processing.
• Stay abreast of industry trends and emerging technologies in data engineering.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, or a related field.
• Proven experience in software development with a strong emphasis on data infrastructure.
• Hands-on experience with Apache Kafka and its ecosystem.
• Strong programming skills in languages such as Java, Python, or Scala.
• Experience with data modeling, ETL processes, and data warehousing concepts.
• Familiarity with cloud platforms and containerization technologies.
• Excellent problem-solving skills and attention to detail.

Technologies & Tools

The Software Engineer - Data Infrastructure role emphasizes the utilization of several key technologies and tools, including Apache Kafka for data streaming, along with frameworks and libraries that complement big data solutions. Experience with cloud services such as AWS or Google Cloud Platform, as well as database technologies like PostgreSQL and NoSQL databases, is also essential. Familiarity with containerization tools like Docker and orchestration platforms such as Kubernetes will enhance your effectiveness within this position.

Ideal Candidates

Ideal candidates for this position will possess a strong analytical mindset with a proven ability to tackle complex data challenges effectively. They will be self-motivated, demonstrating an eagerness to learn and adapt in a fast-paced environment. Outstanding communication and collaboration skills are crucial, as the role involves working closely with various stakeholders. The ability to thrive under pressure while maintaining a focus on delivering quality solutions will set successful candidates apart in this dynamic role.