At a Glance
- Tasks: Design and build modern data infrastructure while developing scalable data pipelines.
- Company: Leading global investment platform with a focus on private markets.
- Benefits: Competitive salary of £130k plus bonus, with opportunities for growth.
- Other info: Join a dynamic team where data drives strategic decision-making.
- Why this job: Shape the future of data strategy in a fast-scaling private credit business.
- Qualifications: Strong programming skills in Python and SQL, with experience in Azure and ML.
The predicted salary is between 130000 - 130000 € per year.
A leading global investment platform is building out its Private Markets capability and is looking to hire a high-impact Investment Data Engineer (VP level) to join its London team. This is a rare opportunity to step into a foundational data role within a fast-scaling private credit business—where you'll shape architecture, analytics, and data strategy from the ground up.
The Opportunity
You'll take ownership of the end-to-end data ecosystem supporting a growing private credit platform, working at the intersection of engineering, analytics, and investment decision-making. This role combines hands-on technical delivery with strategic influence, offering direct exposure to deal teams, fundraising activity, and portfolio monitoring.
Key Responsibilities
- Lead the design and build of modern data infrastructure across SQL Server and Azure (Data Lake, Databricks)
- Develop scalable data pipelines and integrate multiple internal and external systems
- Create intuitive front-end tools and workflows to drive user adoption across the business
- Build and deploy machine learning models (text extraction, deal sourcing, portfolio monitoring)
- Own and evolve portfolio data pipelines, expanding coverage across live and historical deals
- Establish data governance frameworks and data quality processes from scratch
Candidate Profile
We're looking for a technical self-starter who thrives in a build environment:
- Strong programming skills across Python, SQL
- ML modelling experience
- Proven experience building production-grade data platforms in Azure
- Experience deploying machine learning models into live environments
- Exposure to data governance and data quality frameworks
- Ability to engage business users and deliver user-facing tools and insights
- Background in financial services, private credit, or asset management is advantageous
Why Apply?
- Build a greenfield data architecture within a high-growth investment platform
- Work directly with investment professionals on deal-critical analytics
- Gain exposure to front-office decision-making and fundraising activity
- Join a team where data is central to strategy, not just reporting
Investment Data Engineer (VP) - SQL. ML, Azure - London : £130k + bonus employer: Hunter Bond
Join a leading global investment platform in London, where you'll have the unique opportunity to shape the data architecture and strategy for a fast-scaling private credit business. With a strong focus on employee growth, our collaborative work culture encourages innovation and direct engagement with investment professionals, ensuring that your contributions are valued and impactful. Enjoy competitive compensation, including a generous bonus structure, while working in an environment that prioritises data-driven decision-making and offers a chance to build cutting-edge solutions from the ground up.
StudySmarter Expert Advice🤫
We think this is how you could land Investment Data Engineer (VP) - SQL. ML, Azure - London : £130k + bonus
✨Tip Number 1
Network like a pro! Reach out to professionals in the investment and data engineering space on LinkedIn. Join relevant groups and participate in discussions to get your name out there and show your expertise.
✨Tip Number 2
Prepare for those interviews by brushing up on your technical skills. Be ready to discuss your experience with SQL, Azure, and machine learning models. We recommend doing mock interviews with friends or using online platforms to practice.
✨Tip Number 3
Showcase your projects! If you've built any data pipelines or machine learning models, make sure to have them ready to discuss. We love seeing real-world applications of your skills, so bring your portfolio to the table.
✨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 candidates who want to shape the future of data in investment.
We think you need these skills to ace Investment Data Engineer (VP) - SQL. ML, Azure - London : £130k + bonus
Some tips for your application 🫡
Tailor Your CV:Make sure your CV speaks directly to the role of Investment Data Engineer. Highlight your experience with SQL, Azure, and machine learning, and don’t forget to showcase any relevant projects that demonstrate your skills in building data platforms.
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re excited about this opportunity and how your background aligns with the company's goals. Be sure to mention your passion for data and how you can contribute to shaping their data strategy.
Showcase Your Technical Skills:In your application, be specific about your technical expertise. Mention your programming skills in Python and SQL, and provide examples of how you've built scalable data pipelines or deployed machine learning models in previous roles.
Apply Through Our Website:We encourage you to apply through our website for a smoother process. It helps us keep track of your application and ensures you don’t miss out on any important updates. Plus, it shows you’re keen on joining our team!
How to prepare for a job interview at Hunter Bond
✨Know Your Tech Inside Out
Make sure you’re well-versed in SQL, Python, and Azure. Brush up on your experience with data pipelines and machine learning models, as these will be key topics during the interview. Be ready to discuss specific projects where you've built production-grade data platforms.
✨Showcase Your Strategic Thinking
This role is about more than just technical skills; it’s about shaping data strategy. Prepare examples of how you've influenced data architecture or governance frameworks in previous roles. Highlight your ability to engage with business users and deliver insights that drive decision-making.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving skills in real-world scenarios. Think about challenges you've faced in building data infrastructure or deploying machine learning models, and how you overcame them. Use the STAR method (Situation, Task, Action, Result) to structure your answers.
✨Understand the Business Context
Familiarise yourself with the private credit market and the investment platform's goals. Being able to discuss how data impacts fundraising and portfolio monitoring will show your understanding of the business. This knowledge can set you apart from other candidates who may focus solely on technical skills.
