Software Engineer - Data Infrastructure - Kafka

Canonical is building a comprehensive automation suite to provide multi-cloud and on-premise data solutions for the enterprise. The data platform team is a collaborative team that develops a managed solutions for a full range of data stores and data technologies, spanning from big data, through NoSQL,  cache-layer capabilities, and analytics; all the way to structured SQL engines (similar to Amazon RDS approach). 

We are facing the interesting problem of fault-tolerant mission-critical distributed systems and intend to deliver the world's best automation solution for delivering managed data platforms. 

We are looking for candidates from junior to senior level with interests, experience and willingness to learn around Big Data technologies, such as distributed event-stores (Kafka) and parallel computing frameworks (Spark). Engineers who thrive at Canonical are mindful of open-source community dynamics and equally aware of the needs of large, innovative organisations.

Location: This role can be filled in European, Middle East and African time zones.

What your day will look like

The data platform team is responsible for the automation of data platform operations, with the mission of managing and integrating Big Data platforms at scale. This includes ensuring fault-tolerant replication, TLS, installation, backups and much more; but also provides domain-specific expertise on the actual data system to other teams within Canonical. This role is focused on the creation and automation of infrastructure features of data platforms, not analysing and/or processing the data in them.

• Collaborate proactively with a distributed team

• Write high-quality, idiomatic Python code to create new features

• Debug issues and interact with upstream communities publicly

• Work with helpful and talented engineers including experts in many fields

• Discuss ideas and collaborate on finding good solutions

• Work from home with global travel for 2 to 4 weeks per year f...