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- Tasks: Build and maintain scalable data pipelines for complex datasets and collaborate with AI/ML teams.
- Company: Dynamic tech company based in Edinburgh, fostering innovation and collaboration.
- Benefits: Competitive hourly rate, flexible remote work, and potential for contract extension.
- Why this job: Join a cutting-edge team and work on impactful data projects that drive AI advancements.
- Qualifications: Strong Data Engineering background with experience in big data environments and data modelling.
- Other info: Onsite work required 3 days a week in Edinburgh, with excellent growth opportunities.
The predicted salary is between 36000 - 60000 £ per year.
Onsite: 3 days per week – mandatory
Remote Start: ASAP
Duration: 12-24 months (extension very likely)
Language: English (must-have)
What you’ll do:
- Build and maintain scalable data pipelines for large, complex datasets
- Work hands-on with structured & unstructured data across multiple sources
- Ensure data quality, reliability and performance end-to-end
- Collaborate closely with AI / ML teams to deliver model-ready datasets
- Support data governance, lineage and documentation (pragmatic, not bureaucratic)
What you bring:
- Strong Data Engineering background (senior level)
- Experience with big data environments (e.g. Spark, distributed systems, cloud data platforms)
- Solid understanding of data modelling, ETL/ELT, pipelines
- Comfortable working onsite in Edinburgh 3x/week
Nice to have:
- Exposure to ML / AI data workflows
- Experience with orchestration tools (Airflow / similar)
- Cloud experience (AWS / Azure / GCP)
What we need:
If you are interested and available – or if you know someone you would recommend – I’d be happy to receive your updated CV with a short email incl. contact details.
Please always include:
- Availability start date
- Hourly rate (Edinburgh & Remote)
- A short 2–3 line summary explaining why your background is a good fit for this project
Data Engineer employer: WorkGenius Group
Contact Detail:
WorkGenius Group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer
✨Tip Number 1
Network like a pro! Reach out to your connections in the data engineering field and let them know you're on the lookout for opportunities. You never know who might have a lead or can put in a good word for you.
✨Tip Number 2
Get your hands dirty with some projects! Build a portfolio showcasing your skills in data pipelines, ETL processes, and any big data tools you've worked with. This will give you something tangible to discuss during interviews.
✨Tip Number 3
Prepare for those interviews! Brush up on your technical knowledge and be ready to discuss your experience with cloud platforms and orchestration tools. Practice common interview questions related to data engineering to boost your confidence.
✨Tip Number 4
Apply through our website! We love seeing candidates who take the initiative. Make sure to tailor your application to highlight your relevant experience and why you're a great fit for the role. Don't forget to include your availability and hourly rate!
We think you need these skills to ace Data Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your strong Data Engineering background and experience with big data environments. We want to see how your skills align with the job description, so don’t be shy about showcasing relevant projects!
Craft a Compelling Email: When you send your application, include a short email that captures our attention. A 2-3 line summary explaining why you're a great fit for this role can make all the difference. Keep it concise and engaging!
Be Clear About Availability: Don’t forget to mention your availability start date in your email. We’re looking to get someone on board ASAP, so being upfront about when you can start helps us a lot!
Show Your Enthusiasm: Let us know why you’re excited about this opportunity! A little enthusiasm goes a long way, so share what draws you to the role and how you see yourself contributing to our team.
How to prepare for a job interview at WorkGenius Group
✨Know Your Data Inside Out
Make sure you’re well-versed in the data engineering concepts relevant to the role. Brush up on your experience with big data environments like Spark and distributed systems, as well as your understanding of ETL/ELT processes. Being able to discuss specific projects where you've built scalable data pipelines will definitely impress.
✨Showcase Collaboration Skills
Since the role involves working closely with AI and ML teams, be prepared to talk about your collaborative experiences. Share examples of how you’ve worked with cross-functional teams to deliver model-ready datasets. Highlighting your ability to communicate effectively with different stakeholders can set you apart.
✨Demonstrate Problem-Solving Abilities
Data engineering often involves troubleshooting and optimising data quality and performance. Be ready to discuss challenges you’ve faced in previous roles and how you overcame them. This shows that you can handle the complexities of large datasets and maintain reliability end-to-end.
✨Prepare for Technical Questions
Expect technical questions related to data modelling, cloud platforms, and orchestration tools like Airflow. Brush up on these topics and be ready to explain your thought process. Practising coding problems or case studies can also help you feel more confident during the interview.
