IoT/Data Platform Engineer

As an IoT/Data Platform Engineer at Canonical, you will take on key responsibilities including collaborating with a globally distributed team, architecting scalable service APIs for streaming data services, and developing robust data governance and auditing systems within our telemetry platform. You'll be integral in building both cloud-based SaaS offerings and containerized solutions, as well as implementing features from specification to production.

To thrive as an IoT/Data Platform Engineer at Canonical, candidates should hold a Bachelor’s degree in Computer Science or a similar STEM field. Additionally, a solid understanding of data streaming technologies, cybersecurity in IoT environments, and proficiency in backend development using Python and Golang are crucial for success in this role.

Canonical is deeply committed to employee development. As an IoT/Data Platform Engineer, you’ll benefit from learning and development allowances, enabling you to explore emerging technologies. Canonical also emphasizes personal growth through regular annual compensation reviews and recognition rewards for your contributions.

The work culture at Canonical as an IoT/Data Platform Engineer is dynamic, inclusive, and remote-first. You'll be part of a unique team of over 1000 professionals from 70+ countries, where diversity of experience and perspectives foster innovation. Your work will be collaborative and engaging, driven by a passion for open source software.

An IoT/Data Platform Engineer at Canonical should have experience with telemetry and connectivity systems, including MQTT, Kafka, and RabbitMQ, as well as familiarity with industrial data exchange protocols like OPC-UA and ModBus. Knowledge of data governance models and proficiency in designing REST APIs is also essential to succeed in this role.

When asked about your experience with data streaming technologies, highlight specific tools you've used, like MQTT or Kafka. Discuss how you have implemented these technologies in previous projects to drive efficiency and reliability in data transmission.

In responding to your approach to developing scalable APIs, emphasize your methodology, such as using microservices architecture and how you ensure that the APIs can handle increased loads. Provide examples of past projects to illustrate your point.

Discuss the importance of data governance in IoT and provide examples of how you have implemented governance frameworks that protect data integrity and adhere to compliance standards in past roles.

Share your remote collaboration techniques, such as using communication tools for regular check-ins, setting clear expectations, and leveraging collaborative software for coding and project management to keep the team engaged and informed.

When describing a challenging problem, focus on the problem-solving steps you took. Highlight how you analyzed the issue, the strategies you implemented to find a solution, and the outcomes of your actions.

Be honest about your programming proficiency. Discuss your expertise in languages such as Python or Golang, and any relevant tools or frameworks you’ve mastered, emphasizing how they apply to the IoT/Data Platform Engineer role.

Explain your methods for staying updated on industry trends, such as subscribing to tech journals, participating in webinars, and engaging in forums. Mention any specific resources or communities that have been beneficial in your learning.

Here, share your insights on challenges such as data security, interoperability, or scalability in IoT ecosystems. Provide thoughtful reasoning to back your points based on your experience and understanding of the field.

If applicable, discuss your contributions to open-source projects, detailing the role you played and the technologies involved. Emphasize how this experience aligns with Canonical's commitment to open source.

Illustrate your time management and prioritization strategies. Discuss how you assess project importance, deadlines, and team needs, and how you balance these elements to ensure efficient workflow.