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- Tasks: Build robust data pipelines for AI and machine learning projects.
- Company: Leading enterprise in manufacturing, driving global AI initiatives.
- Benefits: 100% remote work, competitive pay, and potential for full-time conversion.
- Other info: Opportunity to work with innovative technologies and grow your career.
- Why this job: Join a cutting-edge team and shape the future of AI in manufacturing.
- Qualifications: Strong skills in Azure Data Factory, SQL, Python, and Spark.
The predicted salary is between 60000 - 80000 £ per year.
Role: AI Data Engineer
Location: 100% remote
Start date: May 2026
Length: 12 month contract, with option to extend or convert to full time
About: Enterprise manufacturing organisation scaling AI initiatives globally. Looking for a Data Engineer focused on building robust, scalable data pipelines that power ML and AI workloads.
Essential Skills:
- Strong experience with Azure Data Factory and Synapse Analytics
- Proven delivery of data pipelines supporting machine learning workloads
- Strong SQL, Python, and Spark (PySpark preferred)
- Experience working with Azure Data Lake / Blob Storage at scale
- Understanding of data governance, security, and data quality in Azure environments
Nice to have:
- Experience with feature stores or ML data versioning concepts
- Exposure to real-time or streaming data pipelines
AI Data Engineer employer: Darwin Recruitment
Contact Detail:
Darwin Recruitment Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Data Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. We can’t stress enough how personal connections can lead to job opportunities, especially in tech.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data pipelines and projects. We love seeing real examples of what you can do, so make sure to highlight your experience with Azure Data Factory and Synapse Analytics.
✨Tip Number 3
Prepare for those interviews! Brush up on your SQL, Python, and Spark skills. We recommend practicing common interview questions related to data engineering and AI workloads to boost your confidence.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, we’re always on the lookout for talented individuals who can help us scale our AI initiatives globally.
We think you need these skills to ace AI Data Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Azure Data Factory, Synapse Analytics, and any relevant data pipelines you've built. We want to see how your skills align with the role of AI Data Engineer, so don’t hold back!
Showcase Your Projects: Include specific examples of projects where you’ve used SQL, Python, or Spark. If you’ve worked on machine learning workloads, let us know! This is your chance to shine and show us what you can bring to the table.
Be Clear and Concise: When writing your application, keep it straightforward. Use bullet points for key achievements and avoid jargon unless it’s relevant. We appreciate clarity, and it helps us understand your experience better.
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 Darwin Recruitment
✨Know Your Tech Inside Out
Make sure you brush up on your skills with Azure Data Factory, Synapse Analytics, and the other essential tools mentioned in the job description. Be ready to discuss specific projects where you've built data pipelines for machine learning workloads, as this will show your practical experience.
✨Showcase Your Problem-Solving Skills
Prepare to talk about challenges you've faced in previous roles, especially around data governance and security in Azure environments. Companies love candidates who can think critically and provide solutions, so have a few examples ready that highlight your problem-solving abilities.
✨Get Familiar with the Company’s AI Initiatives
Research the enterprise manufacturing organisation and their AI initiatives. Understanding their goals and how your role as an AI Data Engineer fits into their strategy will help you tailor your answers and demonstrate your genuine interest in the position.
✨Ask Insightful Questions
Prepare some thoughtful questions to ask at the end of your interview. Inquire about their current data pipeline challenges or how they envision the role evolving over time. This not only shows your enthusiasm but also helps you gauge if the company is the right fit for you.