Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Design and build data systems from scratch, owning datasets end-to-end.
- Company: Dynamic firm in Abu Dhabi focused on innovative data engineering.
- Benefits: Competitive salary, education allowance, 30 days leave, and comprehensive healthcare.
- Why this job: Join a cutting-edge team solving complex data challenges in finance.
- Qualifications: Strong Python and SQL skills, experience with data pipelines, and a curious mindset.
- Other info: Relocation support provided; enjoy a sustainable work environment.
The predicted salary is between 96000 - 144000 £ per year.
Location: Abu Dhabi, UAE (relocation support provided)
Compensation: £120,000–£300,000 total compensation (fully guaranteed, all-in)
The Role
We are building a centralised data engineering and research platform that supports quantitative research teams across multiple asset classes. This is not an asset-class-specific role, and not a traditional downstream analytics, BI, or ML-only position. The team focuses on large-scale alternative and unstructured data, working from first principles to define the data foundations, tooling, and experimentation standards used across the investment platform. The work involves messy, evolving datasets, performance-sensitive pipelines, and open-ended technical problems. Much of the stack is built in-house and remains largely greenfield.
What You’ll Do
- Design and build data ingestion, validation, and transformation systems from scratch
- Own datasets end-to-end, from raw ingestion through validation and transformation to research-ready delivery and downstream consumers
- Work with financial and alternative datasets used in quantitative research, including structured and unstructured data, large-scale text sources, and other high-dimensional, noisy data where failure modes are not always known upfront
- Build frameworks and tooling to support experimentation
- Optimise systems for correctness, robustness, and performance
- Investigate anomalies, inconsistencies, and data quality issues
- Work directly with quants, researchers, and data scientists in an iterative, research-driven environment
This Role Is a Good Fit If You
- Are strong in Python and SQL, and comfortable working close to raw data
- Have experience building and operating modern data pipelines with real ownership
- Have worked on research-, trading-, or decision-critical systems
- Are curious about modern data tooling (e.g. Polars, Julia, Rust, Lakehouse patterns), even if you haven’t used all of it yet
- Prefer hands-on technical ownership
Ideal Background
- Systematic funds, quantitative asset managers, HFTs, or trading firms
- FinTechs or financial data providers
- Big Tech or adjacent industries where work maps structurally to quant data problems (e.g. large-scale recommender systems, NLP on unstructured data, anomaly detection, knowledge graphs)
- Smaller teams with broad ownership and responsibility
Compensation & Benefits
- Fully guaranteed, competitive compensation
- Education allowance for dependent children
- 30 working days of annual leave, plus public holidays
- Comprehensive healthcare for employee and family
- Business class relocation flights
- Joining and departure allowances
The role is on-site in Abu Dhabi. Short-term remote work during peak summer months is supported. The working model prioritises sustainability and focused technical work.
Send your CV and a brief summary to dana@durlstonpartners.com
Senior Data Engineer in England employer: Durlston Partners
Contact Detail:
Durlston Partners Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Engineer in England
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those who work with data engineering or quantitative research. A friendly chat can lead to insider info about job openings and even referrals.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving messy datasets or performance-sensitive pipelines. This will give potential employers a taste of what you can do and how you tackle real-world problems.
✨Tip Number 3
Prepare for technical interviews by brushing up on Python and SQL. Practice coding challenges that focus on data manipulation and pipeline design. We all know that hands-on skills are key, so make sure you're ready to demonstrate your expertise!
✨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 take the initiative to connect directly with us.
We think you need these skills to ace Senior Data Engineer in England
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Senior Data Engineer role. Highlight your experience with Python, SQL, and any relevant data pipeline projects. We want to see how your skills align with our needs!
Craft a Compelling Summary: Your summary should grab our attention! Briefly explain why you're the perfect fit for this role, focusing on your hands-on experience and ownership of data systems. Keep it concise but impactful.
Showcase Relevant Experience: When detailing your work history, emphasise your experience with alternative and unstructured data. Mention specific projects where you tackled messy datasets or built performance-sensitive pipelines. We love seeing real-world examples!
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of applications better and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at Durlston Partners
✨Know Your Data Inside Out
Make sure you’re well-versed in the types of data you'll be working with, especially alternative and unstructured datasets. Brush up on your experience with Python and SQL, as these will be crucial in demonstrating your technical skills during the interview.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific examples where you've tackled messy or evolving datasets. Highlight how you approached performance-sensitive pipelines and any open-ended technical problems you've solved. This will show your potential employer that you can handle the challenges of the role.
✨Familiarise Yourself with Modern Tools
Even if you haven’t used all the latest data tools like Polars or Julia, showing curiosity and a willingness to learn can set you apart. Research these tools and be ready to discuss how they could apply to the role, demonstrating your proactive approach to staying current in the field.
✨Engage with the Team Mindset
This role involves collaboration with quants, researchers, and data scientists. Be prepared to talk about your experience working in iterative, research-driven environments. Emphasise your ability to communicate effectively and work closely with others to achieve common goals.