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Data Engineer
Job Posted: an hour ago
Salary: £ Competitive
Job Type: Permanent
Location: London
Expire in: a month
Job Description
Data Engineer | AI-Powered SaaS Scale-Up | London (Hybrid)
Salary - up to £45,000 PA Depending on Experience
London (Hybrid: Monday-Wednesday in office)
JOB REF : J13027
We're working with a fast growing tech company that's helping some of the best known brands in the UK turn first-party data into real business advantage.
To be clear.....This isn't a maintenance role
It's about building, learning, and being part of something that's scaling fast. You'll work alongside talented AI Engineers and Analysts, learning how to productionise data and machine learning at scale, and seeing how clean engineering directly shapes how businesses make decisions.
You'll be hands on with Python, SQL, and cloud (Azure, AWS, or GCP), building structured pipelines, integrating ML outputs, and automating processes that keep data flowing securely and reliably.
This is an amazing opportunity for someone early in their data engineering career who craves exposure to AI, automation, and cloud-based delivery - Not just theory, but the real thing.
If that sounds like your kind of challenge, let's have a chat.
Be brave - make the move
Must haves
• 1+ years in a Data Engineering / Platform role
• Demonstrable experience with DevOps workflows
• Excellent STEM degree (Mathematics, Statistics, Computer Science, Engineering, or similar)
No Sponsorship available . Role not available for post grad VISA holders
#DataEngineering #AI #MachineLearning #Python #DatatechAnalytics
Alternatively, you can refer a friend or colleague by taking part in our fantastic referral schemes! If you have a friend or colleague who would be interested in this role, please refer them to us. For each relevant candidate that you introduce to us (there is no limit) and we place, you will be entitled to our general gift/voucher scheme.
Datatech is one of the UK's leading recruitment agencies in the field of analytics and host of the critically acclaimed event, Women in Data. For more information, visit our website: (url removed)Before You Apply
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