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- Tasks: Build and scale a private credit data platform with cutting-edge technologies.
- Company: Fast-growing investment firm focused on private credit and direct lending.
- Benefits: Competitive salary, hybrid work model, and opportunities for professional growth.
- Other info: Join a lean team with significant autonomy and visibility across the business.
- Why this job: Shape data infrastructure that directly influences investment decisions in finance.
- Qualifications: Degree in Computer Science or related field; strong programming skills in Python and SQL.
The predicted salary is between 60000 - 80000 £ per year.
We’re looking for a highly skilled Investment Data Engineer to help build and scale a private credit data and analytics platform. This is a rare opportunity to shape data infrastructure, analytics, and machine learning capabilities from the ground up—directly influencing investment decisions within a fast-growing private markets environment.
About the Role
You will take ownership of the private credit data ecosystem end-to-end—designing robust backend infrastructure, building intuitive user-facing tools, and delivering advanced analytics that power deal sourcing and portfolio monitoring. This is a hands-on engineering role with significant autonomy and visibility across the business.
What You’ll Be Doing
- Architect and build scalable data platforms using SQL Server and Azure
- Develop end-to-end data pipelines and front-end applications for business users
- Design and deploy machine learning models for text analysis, deal sourcing, and portfolio monitoring
- Expand and optimise data access across a growing portfolio of private credit deals
- Establish data governance frameworks and improve data quality processes
- Enable self-serve MI through tooling, training, and knowledge sharing
- Partner with internal teams and external vendors to deliver critical data solutions
About the Platform
- Backed by institutional capital with a growing European investment footprint
- Focused on private credit and direct lending strategies
- A developing Data & Analytics function evolving into a centre of excellence for data engineering and machine learning
What We’re Looking For
- Degree in Computer Science, Data Science, Software Engineering, or similar
- Strong programming skills in Python, SQL, and C#/.NET or JavaScript
- Experience building production-grade data platforms in Azure (Data Lake, Databricks)
- Proven experience delivering ML models in production data pipelines
- Exposure to data governance and data quality frameworks
- Ability to work independently, drive projects, and operate in an evolving environment
- Desirable: Experience with Alteryx, Microsoft Fabric, and Power BI
- Knowledge of Private Credit, Leveraged Finance, or Asset Management
- Familiarity with DealCloud
Why Apply?
- Opportunity to build systems that directly influence investment decisions
- Work at the intersection of data engineering, machine learning, and finance
- Join a lean, high-impact team with strong growth ambitions
- Play a key role in shaping the future of data within the organisation
Data Engineer in Slough employer: Harrington Starr
Contact Detail:
Harrington Starr Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer in Slough
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. We all know that sometimes it’s not just what you know, but who you know that can land you that dream job.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to data engineering and machine learning. We want to see what you can do, so make it easy for potential employers to find your work.
✨Tip Number 3
Prepare for interviews by practising common technical questions and scenarios. We recommend doing mock interviews with friends or using online platforms. The more comfortable you are, the better you’ll perform!
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Plus, applying directly can sometimes give you an edge over other candidates.
We think you need these skills to ace Data Engineer in Slough
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the Data Engineer role. Highlight your programming skills in Python, SQL, and any relevant experience with Azure or machine learning models. We want to see how you can contribute to our private credit data ecosystem!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about data engineering and how your background aligns with our mission at StudySmarter. Don’t forget to mention any experience you have with data governance or building production-grade platforms.
Showcase Your Projects: If you've worked on any relevant projects, whether in a professional setting or as personal endeavours, make sure to include them. We love seeing practical examples of your work, especially if they involve data pipelines or machine learning models. It gives us a glimpse into your hands-on experience!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows us you’re keen on joining our team at StudySmarter!
How to prepare for a job interview at Harrington Starr
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, like SQL Server, Azure, and Python. Brush up on your programming skills and be ready to discuss how you've used these tools in past projects.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific challenges you've faced in data engineering and how you overcame them. Use examples that highlight your ability to design scalable data platforms and deliver ML models in production.
✨Understand the Business Context
Familiarise yourself with private credit and investment strategies. Being able to connect your technical skills to real-world financial applications will impress interviewers and show that you understand the bigger picture.
✨Ask Insightful Questions
Prepare thoughtful questions about the company’s data governance frameworks and how they optimise data access. This shows your genuine interest in the role and helps you gauge if the company is the right fit for you.