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For Companies At a Glance
- Tasks: Build and maintain scalable data pipelines for cutting-edge AI solutions.
- Company: Join a forward-thinking tech company focused on Agentic AI and MLOps.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Why this job: Be at the forefront of AI technology and make a real impact in the industry.
- Qualifications: Strong Data Engineering experience with Python, SQL, and cloud platforms.
- Other info: Collaborative environment with exciting projects and career advancement potential.
The predicted salary is between 36000 - 60000 £ per year.
We're looking for a Data Engineer with hands-on experience in Agentic AI systems and MLOps to help build scalable data platforms and production-ready AI solutions.
What You'll Do
- Build and maintain scalable batch & streaming data pipelines
- Enable data infrastructure for Agentic AI / LLM-based autonomous systems
- Develop and support MLOps pipelines (training, deployment, monitoring)
- Work with vector databases, RAG pipelines, and real-time data systems
- Collaborate closely with ML, AI, and product teams
What We're Looking For
- Strong experience as a Data Engineer
- Proficiency in Python & SQL
- Experience with Agentic AI, LLMs, or autonomous agents
- Solid understanding of MLOps & CI/CD
- Experience with cloud platforms, Azure
- Familiarity with Spark, Kafka, Airflow, Docker, and Kubernetes
Nice to Have
- Experience with vector databases (Pinecone, FAISS, Weaviate)
- ML platforms like MLflow, Kubeflow, SageMaker
- RAG, embeddings, or knowledge graphs
Data Engineer in Oxford employer: Careerwise
Contact Detail:
Careerwise Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer in Oxford
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on a Data Engineer role that’s perfect for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Agentic AI and MLOps. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge. Be ready to discuss your experience with Python, SQL, and cloud platforms like Azure. Practice common data engineering scenarios to demonstrate your problem-solving skills.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented Data Engineers. Keep an eye on our job listings and make sure your application stands out by tailoring it to the specific role.
We think you need these skills to ace Data Engineer in Oxford
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Agentic AI systems and MLOps. We want to see how your skills align with what we're looking for, so don’t be shy about showcasing your relevant projects!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Tell us why you're passionate about data engineering and how you can contribute to our team. Be specific about your experience with Python, SQL, and any cloud platforms you've worked with.
Showcase Your Projects: If you've worked on any cool projects involving data pipelines or MLOps, make sure to mention them! We love seeing real-world applications of your skills, especially if they relate to the technologies we use.
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 the role. Plus, it’s super easy!
How to prepare for a job interview at Careerwise
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description. Brush up on your Python, SQL, and any tools like Spark or Kafka. Being able to discuss your hands-on experience with these technologies will show that you’re ready to hit the ground running.
✨Showcase Your MLOps Knowledge
Since MLOps is a key part of the role, be prepared to talk about your experience with CI/CD pipelines and how you've implemented them in past projects. Share specific examples of how you’ve developed and supported MLOps pipelines to demonstrate your expertise.
✨Prepare for Scenario Questions
Expect scenario-based questions that assess your problem-solving skills. Think about challenges you’ve faced while building data pipelines or working with autonomous systems, and be ready to explain how you tackled those issues effectively.
✨Collaborate and Communicate
This role involves working closely with ML, AI, and product teams, so highlight your collaboration skills. Be ready to discuss how you’ve worked in cross-functional teams and how you communicate complex technical concepts to non-technical stakeholders.
