At a Glance
- Tasks: Build enterprise automation for data platforms and collaborate with a global team.
- Company: Join Canonical, a leader in open-source technology.
- Benefits: Remote work options, competitive salary, and opportunities for travel.
- Other info: Dynamic role with opportunities for professional growth and travel.
- Why this job: Make an impact in the open-source community while working with cutting-edge data technologies.
- Qualifications: Experience with Python and data stores, plus a passion for collaboration.
Canonical is hiring a Software Engineer for Data Infrastructure focused on OpenSearch/Elasticsearch. The role is London-on-site and involves building enterprise automation for data platforms, collaborating with an internationally distributed team, and contributing to open-source communities.
You will write Python, work on data stores, and participate in cloud/on-prem solutions. Travel for internal and external events is required; remote work considerations apply for global teams.
#J-18808-LjbffrData Infrastructure Engineer (OpenSearch/Elasticsearch) - Remote employer: Meetborderless
Stripe is an exceptional employer that fosters a collaborative and innovative work culture, making it an ideal place for a Strategic Sales Compensation Analyst. With a focus on employee growth and development, you will have access to numerous opportunities to enhance your skills while working in a dynamic environment that values transparency and teamwork. Located in a vibrant tech hub, Stripe offers unique advantages such as flexible working arrangements and a commitment to diversity and inclusion, ensuring that every team member feels valued and empowered.
StudySmarter Expert Advice🤫
We think this is how you could land Data Infrastructure Engineer (OpenSearch/Elasticsearch) - Remote
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Meetborderless!
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✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Meetborderless.
✨Apply Directly through Our Website
When you find a suitable opening like Data Infrastructure Engineer (OpenSearch/Elasticsearch) - Remote at Meetborderless, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Craft a Tailored Cover Letter:For a full-time role at Meetborderless, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Meetborderless. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Meetborderless
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
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✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
