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- Tasks: Build and maintain data structures for investment monitoring and reporting.
- Company: Dynamic financial services organisation backed by private equity.
- Benefits: Competitive salary, delivery bonus, and hybrid working options.
- Other info: Hands-on role with visibility to senior decision-makers and excellent growth potential.
- Why this job: Make a real impact on investment decisions with your technical skills.
- Qualifications: 3-5 years in data engineering with strong Python and database experience.
The predicted salary is between 75000 - 85000 £ per year.
Location: London (Hybrid working)
Salary: £75,000 - £85,000 + benefits + Delivery Bonus
We are supporting a PE‑backed financial services organisation with a sizeable balance sheet and a growing institutional investment platform. The business operates in regulated financial services, with a strong focus on long‑term asset management and capital efficiency.
Backed by private equity, the organisation is in a build‑out phase of its central investment capabilities, investing heavily in data, analytics and automation to support portfolio oversight, risk management and decision‑making.
The role sits within a central investment function based in London and works closely with senior stakeholders across investments, risk and finance.
The Role
The business is hiring an Investment Data Engineer (Senior Associate) into its central investment office. This role is responsible for building and maintaining the data structures, analytics and workflows that support investment monitoring, reporting and portfolio analysis. You will partner directly with investment professionals and risk stakeholders, translating business needs into robust technical solutions.
You will work alongside a peer data developer, with shared ownership for the investment data stack and analytics toolkit. This is a genuinely hands‑on role with visibility to senior decision‑makers, suited to someone who wants their technical output to directly inform investment discussions.
Key Responsibilities
- Design and maintain data architecture for structured and unstructured investment data
- Define, source and automate data feeds including market data, portfolio data and reporting outputs
- Develop production‑quality Python analytics for portfolio analysis, monitoring and reporting
- Deliver automated reporting and insight via Power BI or comparable analytics tools
- Partner with investment, risk and finance teams to translate requirements into scalable data solutions
Experience & Skills
- 3–5 years’ experience in a data engineering, analytics engineering or investment data role
- Strong Python skills used in a disciplined, production environment
- Solid experience working with databases and data pipelines
- Exposure to modern data platforms such as Snowflake or Databricks, including use of AI tooling across structured and unstructured data
- Working knowledge of financial markets; fixed income or rates exposure beneficial but not essential
If this role is of interest to you please apply below or reach out for more information.
Data Engineer employer: Dartmouth Partners
Contact Detail:
Dartmouth Partners 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 events. 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 data projects, especially those using Python and analytics tools. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and understanding of financial markets. Be ready to discuss how your experience aligns with the role's requirements.
✨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 hearing from passionate candidates like you!
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 experience with Python, data architecture, and any relevant projects that showcase your skills in analytics and reporting.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about investment data engineering and how your background aligns with our needs. Be specific about your achievements and how they relate to the role.
Showcase Your Technical Skills: Don’t forget to mention your technical skills clearly. If you’ve worked with databases, data pipelines, or tools like Power BI, make sure these are front and centre. We want to see how you can contribute to our data stack!
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at Dartmouth Partners
✨Know Your Data Inside Out
Make sure you’re well-versed in the data architecture and analytics tools mentioned in the job description. Brush up on your Python skills and be ready to discuss how you've used them in previous roles, especially in a production environment.
✨Understand the Business Context
Familiarise yourself with the financial services sector, particularly around investment management. Knowing how data impacts decision-making in this space will help you connect with your interviewers and demonstrate your interest in the role.
✨Prepare for Technical Questions
Expect to face technical questions related to data pipelines, databases, and modern data platforms like Snowflake or Databricks. Practise explaining your past projects and how you’ve tackled challenges in these areas to show your problem-solving skills.
✨Showcase Your Collaboration Skills
Since the role involves partnering with various teams, be prepared to discuss examples of how you’ve successfully collaborated with stakeholders in the past. Highlight your ability to translate business needs into technical solutions, as this is key for the position.