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- Tasks: Build and maintain cloud infrastructure while collaborating with data scientists.
- Company: Leading data analytics company in the UK with a focus on innovation.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Why this job: Join a dynamic team and work on impactful data-driven projects.
- Qualifications: 2-4 years of software engineering experience with AWS and Python skills.
- Other info: Exciting challenges await in a collaborative and rewarding environment.
The predicted salary is between 40000 - 48000 £ per year.
A data analytics company in the United Kingdom is seeking a Software Engineer with expertise in AWS and Python to strengthen their AI & Data Ops team. The role involves building and maintaining pivotal internal systems and cloud infrastructure while collaborating with data scientists and engineers.
Ideal candidates will have 2–4 years of experience in software engineering, strong technical skills, and a collaborative mindset. This position promises a challenging yet rewarding environment to contribute to data-driven projects.
Production AI & Data Ops Engineer (Python/AWS) employer: Oxford Data Plan
Contact Detail:
Oxford Data Plan Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Production AI & Data Ops Engineer (Python/AWS)
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at local meetups. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a GitHub profile showcasing your Python projects or any AWS work you've done. This gives potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for those interviews! Brush up on common technical questions related to Python and AWS, and be ready to discuss your past projects. Practice makes perfect, so consider mock interviews with friends or mentors.
✨Tip Number 4
Don't forget to apply through our website! We’ve got loads of opportunities that might just be the perfect fit for you. Plus, it’s a great way to get noticed by our hiring team directly.
We think you need these skills to ace Production AI & Data Ops Engineer (Python/AWS)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Python and AWS. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re excited about joining our AI & Data Ops team and how your collaborative mindset can contribute to our data-driven projects.
Showcase Your Problem-Solving Skills: In your application, give examples of how you've tackled challenges in previous roles. We love seeing candidates who can think critically and come up with innovative solutions!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity!
How to prepare for a job interview at Oxford Data Plan
✨Know Your Tech Inside Out
Make sure you brush up on your Python and AWS skills before the interview. Be ready to discuss specific projects where you've used these technologies, as well as any challenges you faced and how you overcame them.
✨Show Off Your Collaboration Skills
Since this role involves working closely with data scientists and engineers, be prepared to share examples of how you've successfully collaborated in the past. Highlight your ability to communicate complex ideas clearly and work as part of a team.
✨Understand the Company’s Data Vision
Do some research on the company’s data-driven projects and their overall mission. This will not only help you answer questions more effectively but also show your genuine interest in contributing to their goals.
✨Prepare for Problem-Solving Questions
Expect technical questions that assess your problem-solving abilities. Practice coding challenges or system design scenarios related to AI and data operations, as this will demonstrate your analytical thinking and technical prowess.