Harnham
Chief Data Officer

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Chief Data Officer
£150,000 - £180,000
London | Hybrid (1 day per week in the office)
The Business
Our client is a rapidly expanding, private equity-backed financial services organisation undergoing a significant period of growth and transformation. With substantial investment being made across data, technology, and digital products, the business is looking to appoint an experienced data executive to help shape and scale its future capabilities. This is a high-profile leadership position with responsibility for evolving the organisation's data landscape, strengthening engineering capabilities, and unlocking greater value from data throughout the customer lifecycle.
The Opportunity
As Chief Data Officer, you will own the organisation's data strategy and lead the continued evolution of its data and analytics function. Working alongside the Executive Leadership Team, you will help position data at the centre of business decision-making and future growth.
Key responsibilities will include:
- Assessing and evolving the current data operating model, team structure, and overall capability.
- Developing and delivering a long-term data strategy aligned with wider business objectives.
- Driving the implementation of a modern cloud-based data platform, including lakehouse and warehouse solutions.
- Creating a scalable self-service data capability that enables teams to access trusted insights efficiently.
- Enhancing data engineering, architecture, governance, and analytical maturity across the business.
- Partnering closely with technology, product, and commercial leaders to promote a data-led culture.
- Exploring the use of AI and automation to improve operational efficiency, engineering effectiveness, and business performance.
- Delivering customer-focused data initiatives across onboarding, personalisation, insight generation, and customer engagement.
- Embedding robust, scalable, and secure data practices that support long-term growth.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Background & Experience:


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- Demonstrable experience within a senior data leadership role, such as Data Director, VP Data, Head of Data, or Chief Data Officer.
- Experience working within digitally enabled or technology-led organisations.
- Proven success leading large-scale data transformation programmes and building high-performing data functions.
- Strong expertise across data engineering, architecture, analytics, cloud technologies, and modern data platforms.
- Hands-on experience implementing data lakes, cloud data solutions, and enterprise-scale data warehousing environments.
- Track record of delivering self-service reporting and data products that drive business adoption and value.
- Ability to engage and influence stakeholders at executive, strategic, and technical levels.
- Strong understanding of contemporary data technologies and engineering best practices.
- Exposure to Azure and the wider Microsoft data ecosystem would be advantageous.
- Good appreciation of AI, automation, and their practical application within engineering and business environments.
- Experience collaborating across architecture, engineering, product, and executive leadership teams.
- Commercially focused with the ability to combine strategic thinking with pragmatic delivery.
- Prior experience within financial services, lending, payments, fintech, or another regulated industry would be beneficial.
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