Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Build and scale a private credit data platform, influencing investment decisions.
- Company: Fast-growing investment firm with a focus on private credit and analytics.
- Benefits: Hybrid work model, competitive salary, and opportunities for professional growth.
- Other info: Join a dynamic team with ambitions for growth and innovation.
- Why this job: Shape data infrastructure and make a real impact in finance and analytics.
- Qualifications: Degree in Computer Science or related field; strong programming skills required.
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 employer: Harrington Starr
Contact Detail:
Harrington Starr 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 folks in the industry on LinkedIn or at meetups. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving SQL, Python, and Azure. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on common data engineering questions and practical scenarios. We recommend doing mock interviews with friends or using online platforms to get comfortable.
✨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 love seeing candidates who are proactive!
We think you need these skills to ace Data Engineer
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 scalable 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 hands-on experience, especially if it involves building data pipelines or deploying machine learning models. It gives us a glimpse of what you can bring to the table!
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, especially SQL Server, Azure, and programming languages like Python and C#. Brush up on your knowledge of data pipelines and machine learning models, as these will likely come up during technical discussions.
✨Showcase Your Projects
Prepare to discuss specific projects where you've built data platforms or developed analytics tools. Be ready to explain your role, the challenges you faced, and how you overcame them. This will demonstrate your hands-on experience and problem-solving skills.
✨Understand the Business Context
Familiarise yourself with private credit and asset management concepts. Being able to relate your technical skills to real-world investment decisions will show that you understand the bigger picture and can contribute meaningfully to the team.
✨Ask Insightful Questions
Prepare thoughtful questions about the company’s data governance frameworks and how they plan to scale their data infrastructure. This not only shows your interest in the role but also gives you a chance to assess if the company aligns with your career goals.