Junior Data Engineer
CanonicalHome based - EMEAPosted 21 February 2026
Job Description
Junior Data Engineer
Bring your data analytics and data mining skills to a unique team seeking to understand and shape the future of marketing technology. We are interested in technology adoption patterns, the respect of visitors' data and the use of open source in marketing. We are also interested in those marketing data analysts who are curious enough to embrace new technologies and are ready to work with unfamiliar tools, if needed.
The role of a Junior Data Engineer at Canonical
Canonical has provided developers with open source since 2004, helping them build innovations such as public cloud, machine learning, robotics or blockchain. Marketing at Canonical means being at the forefront of innovation, for our customers and for our own martech stack. We’re on the look out for a marketing data analyst to join our team and execute on our growth hacking strategy.
The ideal candidate will be passionate about technology, technology marketing and the use of technology in marketing. You will prefer to work in an environment that has emphasis on ownership of campaigns, collaboration, learning, curiosity and a drive to continually improve oneself / the team / the organisation. You will also love to problem solve, get hands-on, experiment, measure and use automation to make daily life easier.
The Marketing team at Canonical drives commercial outcomes for the company across its portfolio of products and grows the addressable market through digital marketing campaigns, lifecycle management, events, partnerships and community development. If these things are important to you and you're motivated by driving data engineering, delighting customers and filling the sales funnel, we want to talk with you.
This role sits in the Marketing team reporting to the Growth Engineering Manager.
Location: This role will be based remotely in the EMEA region.
What your day will look like
Utilise advanced data analytics to grow Canonical’s product adoption and market penetration
Design and conduct experiments with data, visualisation and insights into Canonical’s target audiences
Build a marketing data stack based on open source, and integrate it with our data mesh
Collaborate with stakeholder teams (Product Management, Engineering, Information Systems, Finance, RevOps, etc) to improve the data and tool ecosystem
Put in place and maintain systems to ensure teams across the company have self-service access to data dashboards
What we are looking for in you?
Background in data science, mathematics, actuarial science, or engineering
Up to 1 year of experience in data analytics
Knowledge in advanced statistics, data sciences, coding/scripting languages (Python, JS, etc), and databases (SQL, etc)
Strength in data visualisation tools (Looker Studio, Tableau, Apache Superset, etc)
Ability to translate business questions to key research objectives
Ability to identify the best methodology to execute research, synthesise and analyse findings
Excellent writing and communication skills
Willingness to examine the status quo and resilient in the face of challenges
What we offer you
Your base pay will depend on various factors including your geographical location, level of experience, knowledge and skills. In addition to the benefits above, certain roles are also eligible for additional benefits and rewards including annual bonuses and sales incentives based on revenue or utilisation. Our compensation philosophy is to ensure equity right across our global workforce.
In addition to a competitive base pay, we provide all team members with additional benefits, which reflect our values and ideals. Please note that additional benefits may apply depending on the work location and, for more information on these, you can ask in the later stages of the recruitment process.
🏠Fully remote working environment - we’ve been working remotely since 2004!
📚Personal learning and development budget of 2,000 USD per annum
💰Annual compensation review
🏆Recogn ... (truncated, view full listing at source)
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