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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: Dynamic team 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 Hull employer: Careerwise
Contact Detail:
Careerwise Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer in Hull
✨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 job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Agentic AI and MLOps. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills. Be ready to discuss your experience with Python, SQL, and cloud platforms like Azure. Practice common data engineering scenarios to demonstrate your problem-solving abilities.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Data Engineer in Hull
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! Use it to explain why you're passionate about data engineering and how you can contribute to our team. Keep it engaging and personal – we love getting to know the real you.
Showcase Your Technical Skills: Be specific about your proficiency in Python, SQL, and any cloud platforms you've worked with. Mention your experience with tools like Spark, Kafka, or Docker, as these are key to the role. We want to see your technical prowess!
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 makes the process smoother for everyone involved!
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, prepare to discuss your experience with building and maintaining pipelines. Be ready to share specific examples of how you've deployed and monitored models in production. This will demonstrate your understanding of the end-to-end process.
✨Prepare for Scenario Questions
Expect scenario-based questions that test your problem-solving skills. Think about challenges you've faced in previous roles, especially related to data pipelines or AI systems. Practising your responses can help you articulate your thought process clearly during the interview.
✨Collaborate and Communicate
Since collaboration with ML, AI, and product teams is crucial, be prepared to discuss how you’ve worked in cross-functional teams before. Highlight your communication skills and how you ensure everyone is on the same page when working on complex projects.
