Posted on 7 October 2026
£85,000 – £100,000
Permanent
Bedfordshire
33116
Opportunity description
Job Title:
Data Platform Manager
Data Platform Manager
Department: TechnologyReports to: Head of Data, Analytics & AI
Direct Reports: Data Engineers (3)
Location: Bedfordshire (1 day per week in office)
Base Salary: £85,000 – £100,000 plus bonus and other benefits
Contract: Permanent, Full-Time
Stanton House is partnering with a private equity-backed business currently undergoing a significant transformation journey and looking to appoint a Data Platform Manager to lead the evolution of its enterprise data platform.
This is a hands-on leadership role responsible for the design, development and continuous improvement of the organisation's modern data platform. You will own the architecture and delivery of data ingestion, orchestration, warehousing and transformation capabilities, ensuring solutions are scalable, reliable, cost-effective and trusted across the business.
Working at the intersection of strategy and delivery, you will combine technical leadership with active involvement in engineering, architecture, code reviews and platform development, while building and mentoring a high-performing team. A key focus of the role will be driving the adoption of AI-enabled development practices to improve productivity, quality and efficiency while ensuring robust governance, security and control frameworks.
Key Responsibilities
Leadership & Team Management
- Lead, mentor and develop a team of Data Engineers, managing priorities, workloads and sprint delivery.
- Provide hands-on technical leadership and establish engineering best practices.
- Support recruitment, onboarding, performance management and career development.
- Foster a culture of collaboration, continuous improvement, knowledge sharing and code quality.
- Champion the effective and responsible use of AI-assisted development tools.
- Own the architecture, roadmap and ongoing development of the enterprise data platform.
- Design and deliver scalable data warehouses, pipelines and data products.
- Establish standards for data modelling, testing, documentation, deployment and monitoring.
- Lead CI/CD processes, automated testing and release management.
- Provide code reviews and architectural guidance to ensure engineering excellence.
- Integrate new data sources using API, event-driven and file-based ingestion methods.
- Partner with analytics and BI teams to deliver reliable and trusted data assets.
- Drive the adoption of AI tools and coding assistants within the data engineering function.
- Leverage AI to improve development efficiency, testing, documentation and code quality.
- Establish governance frameworks covering responsible AI use, security and data protection.
- Evaluate emerging technologies and identify opportunities to enhance platform capabilities.
- Maintain architecture documentation, technical standards and data lineage.
- Ensure compliance with security, data protection and audit requirements.
- Support capacity planning, budgeting and resource forecasting.
- Report on platform performance, delivery progress and strategic initiatives.
- Strong hands-on experience building and operating enterprise-scale cloud data platforms.
- Expertise in cloud data warehousing, data modelling, governance, optimisation and cost management.
- Advanced SQL and Python skills with strong software engineering practices.
- Experience with modern data transformation frameworks, analytics engineering and workflow orchestration tools.
- Proven track record delivering CI/CD capabilities for data and analytics platforms.
- Experience adopting AI tools within software or data engineering environments.
- Previous people leadership experience, including coaching, performance management and team development.
- Experience managing or quality-assuring delivery from third-party partners or consultancies.
- Strong stakeholder management skills with the ability to translate business requirements into scalable technical solutions.
- Excellent communication skills, with experience engaging both technical and non-technical audiences.
