At a Glance
- Tasks: Design and build scalable data pipelines for cutting-edge financial research.
- Company: Join a leading tech firm in the heart of Abu Dhabi.
- Benefits: Highly competitive salary, comprehensive healthcare, and generous leave.
- Other info: Relocation support provided; focus on sustainability and technical excellence.
- Why this job: Make an impact with innovative data solutions in a dynamic environment.
- Qualifications: Strong Python and SQL skills; experience with data pipelines.
The predicted salary is between 60000 - 80000 £ per year.
Location: Abu Dhabi, UAE (relocation support provided)
Compensation: Highly competitive, fully guaranteed
The Role
We are building a data engineering function to support quantitative research and production teams working with large-scale financial and alternative data. The work involves messy, evolving datasets, performance-sensitive pipelines, and open-ended technical problems. Much of the stack is built in-house and largely greenfield.
What You’ll Do
- Design and build scalable data pipelines
- Own datasets end-to-end, from ingestion and validation to downstream delivery
- Develop ingestion, transformation, and quality-control frameworks
- Build tooling to support research and experimentation
- Optimise data systems for correctness, reliability, and performance
- Collaborate closely with researchers, quants, and data scientists
This Role Is a Good Fit If You
- Strong Python and SQL skills, comfortable working close to raw data
- Experience building and operating modern data pipelines
- Exposure to research-, trading-, or decision-critical systems
- Independent thinker, comfortable with ambiguity
- Preference for hands-on technical ownership
Ideal Background
- Systematic funds, quantitative asset managers, HFTs, or trading firms
- FinTechs or financial data providers
- Smaller teams with broad ownership and responsibility
- Strong early-career profiles with clear technical depth
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
Seniority level: Mid-Senior level
Employment type: Full-time
Job function: Engineering and Research
Industries: Financial Services, Investment Management, and Capital Markets
Data Engineer employer: DURLSTON PARTNERS
Durlston Partners is an exceptional employer, offering a dynamic work environment in Abu Dhabi where innovation meets financial technology. With highly competitive compensation, comprehensive healthcare, and generous annual leave, employees are supported in both their professional and personal lives. The company fosters a culture of collaboration and technical ownership, providing ample opportunities for growth and development in the rapidly evolving field of data engineering.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those working at Durlston Partners or similar firms. A friendly chat can open doors and give you insights that job descriptions just can't.
✨Tip Number 2
Show off your skills! If you've got a portfolio of projects or GitHub repositories, make sure to highlight them. Real-world examples of your work with Python and SQL can really set you apart from the crowd.
✨Tip Number 3
Prepare for technical interviews by brushing up on data pipelines and system optimisation. Practice explaining your thought process clearly, as collaboration is key in this role. We want to see how you tackle problems!
✨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 that extra step to connect with us directly.
We think you need these skills to ace Data Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Data Engineer role. Highlight your Python and SQL skills, and any experience with data pipelines. We want to see how your background fits with our needs!
Craft a Compelling Summary:In your brief summary, showcase your passion for data engineering and your hands-on experience. Let us know why you're excited about working with messy datasets and performance-sensitive pipelines.
Showcase Your Problem-Solving Skills:We love independent thinkers! In your application, mention specific examples where you've tackled ambiguous technical problems. This will help us see your potential fit in our innovative environment.
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. We can’t wait to hear from you!
How to prepare for a job interview at DURLSTON PARTNERS
✨Know Your Data Inside Out
Before the interview, make sure you’re familiar with the types of datasets you might be working with. Brush up on your Python and SQL skills, and be ready to discuss how you've handled messy or evolving data in the past.
✨Showcase Your Problem-Solving Skills
Prepare to talk about specific technical challenges you've faced and how you approached them. Think about examples where you had to optimise data systems for performance or reliability, as this will resonate well with the role.
✨Collaborate Like a Pro
Since the role involves working closely with researchers and quants, be ready to discuss your experience in collaborative environments. Share examples of how you’ve worked with cross-functional teams to deliver successful projects.
✨Embrace Ambiguity
This position requires an independent thinker who can navigate uncertainty. Prepare to discuss times when you’ve thrived in ambiguous situations, showcasing your ability to take ownership and drive results without clear direction.
