Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Create and maintain Power BI dashboards, translating data into insights for investment decisions.
- Company: Join a global leader in private equity, focused on innovative data and analytics solutions.
- Benefits: Enjoy a collaborative environment, strong leadership support, and the chance to shape a new data function.
- Other info: Opportunity to work in a dynamic team, 4 days in-office, with a salary up to £75,000.
- Why this job: Be part of a greenfield project, making a real impact in a fast-growing sector.
- Qualifications: Experience with Power BI, strong Excel skills, and a passion for data quality are essential.
The predicted salary is between 54000 - 84000 £ per year.
Financial Data Analyst – Private Equity (Data & Analytics Team)
London – 4 days in-office
Up to £75,000
Join a global private equity leader across secondary markets. A niche but fast-growing space with complex data challenges and huge strategic importance.
The Company
This firm is investing heavily in its data and analytics capabilities, with a newly established team spearheading the build of scalable tools and platforms to support better, faster investment decisions. If you're passionate about creating order from chaos, building impactful tools, and making data matter, this role offers a rare opportunity to shape a data function from the ground up.
Key Responsibilities
- Build and maintain Power BI dashboards to track portfolio performance, risk, and cash flows, translating raw data into clear insights.
- Partner with Data Engineering to validate pipelines, ensure data quality, and automate reporting processes.
- Deliver interactive reports that support fund analytics, portfolio oversight, and executive decision-making.
- Handle ad hoc data requests and investigate anomalies, highlighting key trends and issues.
- Collaborate with a Data Steward to define and enforce data management and reconciliation standards.
- Document workflows and promote best practices for consistent, scalable analytics.
- Prepare clear, data-driven presentations for senior stakeholders and investment committees.
Expertise & Qualifications
- Strong experience building dashboards and reports with Power BI, Qlik, or similar tools
- Strong Excel skills, including pivot tables and Power Query
- Solid understanding of data quality practices such as validation, exception reporting, and automation
- Clear communicator with the ability to work across technical and non-technical teams
- Exposure to financial services or private equity is a plus
- Familiarity with Python, Snowflake, or dbt is beneficial but not required
Why Join?
- Greenfield opportunity, help build the firm’s internal BI platform from scratch
- High-impact, visible role in a firm committed to data-driven transformation
- A genuinely collaborative team with a bias for action and iteration, not perfection
- Strong support from leadership and investment teams who want better, faster, cleaner data
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Financial Data Analyst
✨Tip Number 1
Familiarise yourself with Power BI and its advanced features. Since this role heavily relies on building dashboards, showcasing your ability to create impactful visualisations can set you apart during the interview process.
✨Tip Number 2
Brush up on your data quality practices. Understanding validation and exception reporting will not only help you in the role but also demonstrate your commitment to maintaining high standards in data management.
✨Tip Number 3
Network with professionals in the private equity sector. Engaging with industry experts can provide insights into the specific challenges they face, which you can address in your discussions with us during the interview.
✨Tip Number 4
Prepare to discuss how you've previously turned raw data into actionable insights. Being able to share concrete examples of your analytical skills will highlight your fit for a role that focuses on making data matter.
We think you need these skills to ace Financial Data Analyst
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in building dashboards and reports, particularly with Power BI or similar tools. Emphasise your strong Excel skills and any exposure to financial services or private equity.
Craft a Compelling Cover Letter: In your cover letter, express your passion for data analytics and how you can contribute to the firm's data-driven transformation. Mention specific examples of how you've created impactful tools or insights from complex data.
Showcase Your Technical Skills: If you have experience with Python, Snowflake, or dbt, be sure to include this in your application. Even if it's not required, it can set you apart from other candidates.
Prepare for Interviews: Be ready to discuss your previous projects involving data quality practices, validation, and automation. Prepare to explain how you would approach building and maintaining dashboards that support fund analytics and decision-making.
How to prepare for a job interview at Harnham
✨Showcase Your Power BI Skills
Be prepared to discuss your experience with Power BI in detail. Bring examples of dashboards you've built and be ready to explain how they helped drive decision-making. This will demonstrate your technical expertise and your ability to translate data into actionable insights.
✨Understand Data Quality Practices
Familiarise yourself with data quality practices such as validation and exception reporting. Be ready to discuss how you ensure data integrity in your work, as this is crucial for the role. Highlight any past experiences where you improved data quality or automated reporting processes.
✨Communicate Clearly
As a Financial Data Analyst, you'll need to bridge the gap between technical and non-technical teams. Practice explaining complex data concepts in simple terms. During the interview, focus on your communication skills and provide examples of how you've successfully collaborated with diverse teams.
✨Prepare for Scenario-Based Questions
Expect scenario-based questions that assess your problem-solving abilities. Think about past challenges you've faced in data analysis and how you overcame them. This will help you demonstrate your critical thinking skills and your ability to handle ad hoc data requests effectively.