Job Description
Title: Head of Data
Location: Buckinghamshire
Salary: £120,000 + Bonus + Stock Options
Ref: HL12810
Hybrid (3-4 days/week onsite)
Finatal are currently partnered with a tech-led services business undergoing a major data transformation after Private Equity investment. They’re now looking for a Head of Data to define and lead their data strategy, bringing structure, governance, and scalability to an organisation where data is central to every decision. Reporting to the CTO, you’ll lead a growing in-house team of 7 across engineering, analytics and data science. You will shape the future data platform and work closely with teams across the business to deliver meaningful insight and drive the adoption of best-in-class data practices.
Role:
* Build and lead the data strategy, collaborating across tech, product, operations, and leadership to embed data into business decision-making.
* Lead and scale the in-house data team while working alongside a large offshore data function.
* Implement data governance policies, setting ownership, processes, and quality standards across the organisation.
* Own the data platform and integrations, with a strong focus on ETL processes. Being able to roll your sleeves up will be useful as the business continues to scale and bring in more sources of data.
* Oversee analytics and BI delivery across Power BI, stakeholder engagement, and actionable reporting frameworks.
* Support AI and ML initiatives, offering guidance on the adoption of advanced analytics where appropriate.
Requirements:
* Strong experience in a lead or head of data position, developing and presenting data strategies and getting buy-in from the board.
* Strong technical background with experience delivering enterprise-level data platforms and infrastructure (Azure, SQL Server, Databricks, or similar).
* Strong understanding of data engineering, pipeline optimisation, and CDC/ETL best practices.
* Proven leadership of data teams and cross-functional initiatives in complex organisations.
* A strategic mindset with the ability to be hands-on when needed.
* Knowledge of data governance frameworks, ownership models, and policy implementation.
* Interest in AI and machine learning trends, with the ability to support exploratory or early-stage adoption.