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For Companies At a Glance
- Tasks: Design and build data systems from scratch, optimising for performance and quality.
- Company: Leading financial firm in Abu Dhabi with a focus on innovative data solutions.
- Benefits: Competitive salary, education allowance, 30 days leave, comprehensive healthcare, and relocation support.
- Why this job: Join a dynamic team tackling complex data challenges and make a real impact in finance.
- Qualifications: Strong Python and SQL skills, experience with data pipelines, and a passion for modern data tools.
- Other info: On-site role with opportunities for short-term remote work during summer.
The predicted salary is between 100800 - 240000 £ 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 Engineer, Data Engineering in England employer: Durlston Partners
Contact Detail:
Durlston Partners Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Engineer, Data Engineering in England
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with potential colleagues on LinkedIn. We all know that sometimes it’s not just what you know, but who you know that can help you land that dream job.
✨Tip Number 2
Prepare for those interviews by brushing up on your technical skills and understanding the latest trends in data engineering. We recommend doing mock interviews with friends or using online platforms to get comfortable with the process.
✨Tip Number 3
Showcase your projects! Whether it's a GitHub repo or a personal website, having a portfolio of your work can really set you apart. We love seeing hands-on experience, especially when it comes to building data pipelines or working with alternative datasets.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we’re always looking for passionate individuals who are ready to take ownership and dive into exciting data challenges.
We think you need these skills to ace Senior Engineer, Data Engineering in England
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with data engineering, especially in Python and SQL. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or achievements!
Craft a Compelling Summary: When you send your brief summary, keep it concise but impactful. We’re looking for a snapshot of your journey and what makes you a great fit for our team. Let your passion for data shine through!
Showcase Your Problem-Solving Skills: In your application, mention specific examples where you've tackled messy datasets or performance-sensitive pipelines. We love seeing how you approach open-ended technical problems, so share those stories!
Apply Through Our Website: While you can send your CV to the email provided, we encourage you to apply through our website as well. It helps us keep track of applications better and ensures you don’t miss out on any updates!
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 data. Brush up on your experience with messy datasets and be ready to discuss how you've tackled similar challenges in the past.
✨Showcase Your Technical Skills
Be prepared to demonstrate your proficiency in Python and SQL. Bring examples of data pipelines you've built or optimised, and be ready to explain the thought process behind your design choices. This is your chance to shine!
✨Understand the Role's Context
Familiarise yourself with the company's focus on quantitative research and the specific challenges they face. Think about how your background in systematic funds or trading firms aligns with their needs, and be ready to articulate this connection during the interview.
✨Ask Insightful Questions
Prepare thoughtful questions that show your curiosity about modern data tooling and the team’s approach to experimentation. This not only demonstrates your interest but also helps you gauge if the role is the right fit for you.