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- Tasks: Lead the charge in building scalable data quality frameworks and tools.
- Company: Join a forward-thinking organisation focused on data excellence.
- Benefits: Enjoy competitive pay, flexible working options, and growth opportunities.
- Why this job: Make a real impact on how data quality is managed across the enterprise.
- Qualifications: Strong understanding of data quality principles and collaborative skills required.
- Other info: Be part of a dynamic team driving innovation in data management.
The predicted salary is between 36000 - 60000 £ per year.
The Data Quality Capabilities SME role is central to building the foundations for enterprise-wide federated Data Quality. Reporting directly to the Data Quality Capabilities Lead, you will work closely with the Global Head of Data Quality and other senior leaders within the Chief Data Office (CDO) to design and embed the frameworks, tools, and processes that make data quality actionable and scalable. You will act as a strategic delegate for the Group Data Quality vision, providing third-line support and expert guidance to the BAU team.
In the initial phase, you will support organisational change by shaping capabilities that enable federated ownership of data quality across business domains. This includes developing rulebooks, metadata models, profiling mechanisms, and other reusable components that align with strategic objectives and technical realities. The role requires strong collaboration with engineering and business teams to ensure frameworks are robust and practically adopted.
Once this transformation is complete, the role will evolve into a second-line assurance function, providing oversight and governance to ensure federated teams apply data quality standards consistently. You will maintain and enhance the core frameworks, act as an escalation point for complex issues, and safeguard the integrity of the organisation's data quality ecosystem.
This is a highly collaborative role, requiring engagement with engineering, governance, and business teams to ensure alignment and adoption. It is ideal for someone who thrives on bringing clarity to ambiguity, enjoys creating structured solutions, and wants to leave a lasting impact on how data quality is operationalised at scale.
The SME team is distinct from the BAU team, which owns day-to-day management and resolution of DQ issues. The SME team's focus is on strategic enablement, framework design, and third-line escalation, not on building a parallel BAU or engineering function.
Role Responsibilities
- Capability Building & Change Enablement
- Translate Strategy into Action: In conjunction with our change teams, convert high-level data quality concepts into structured delivery plans, frameworks, and reusable components.
- Design & Implement Capabilities: Develop rulebooks, metadata models, profiling mechanisms, and other tools that make data quality measurable and actionable. Leverage technical awareness to ensure frameworks and standards are compatible with modern data platforms and can be effectively implemented by engineering teams.
- Enable Federated Adoption: Shape foundational capabilities that allow decentralised ownership of data quality across business domains, providing subject matter expertise to bridge business requirements and technical implementation.
- Collaborate Across Functions: Work closely with the Data Quality Capabilities Lead, Global Head of Data Quality, and other CDO leaders, as well as engineering, governance, and business teams.
- Document & Communicate: Maintain clear records of designs, decisions, and progress; communicate effectively with stakeholders at all levels.
- Third-Line Support & Assurance: Provide governance and assurance that federated teams apply data quality standards consistently, acting as a point of escalation and guidance for complex or cross-functional issues, and supporting the BAU team as third-line experts.
- Maintain & Evolve Frameworks: Keep rulebooks, metadata models, and tooling up to date with business and technology changes.
- Escalation Point: Act as a subject matter expert for complex data quality issues, drawing on both business context and technical understanding of data quality tools, rule engines, and platform integration.
- Continuous Improvement: Identify opportunities to enhance processes and capabilities based on feedback and performance metrics.
The ideal candidate will possess a blend of business acumen and technical awareness, enabling them to translate strategic objectives into frameworks that are robust and implementable within modern data environments.
Reporting
- Monitor and report on Business Units' issues.
- Provide relevant management information to senior management.
- Any other reasonable duties, as required.
Data Quality Lead employer: Howden
Contact Detail:
Howden Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Quality Lead
✨Tip Number 1
Network like a pro! Reach out to people in your industry on LinkedIn or at events. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Prepare for interviews by researching the company and its culture. Tailor your answers to show how you can contribute to their data quality goals. We want to see your passion!
✨Tip Number 3
Practice makes perfect! Do mock interviews with friends or use online platforms. The more comfortable you are, the better you’ll perform when it counts.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who take that extra step.
We think you need these skills to ace Data Quality Lead
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter to highlight your experience with data quality frameworks and collaboration. We want to see how your skills align with our mission at StudySmarter!
Showcase Your Collaboration Skills: Since this role is all about working with different teams, share examples of how you've successfully collaborated in the past. We love seeing candidates who can bridge gaps between technical and business needs!
Be Clear and Concise: When writing your application, keep it straightforward. Use clear language to describe your achievements and how they relate to the responsibilities outlined in the job description. We appreciate clarity!
Apply Through Our Website: We encourage you to submit your application directly through our website. It’s the best way for us to receive your details and ensures you’re considered for the role. Don’t miss out!
How to prepare for a job interview at Howden
✨Know Your Data Quality Frameworks
Before the interview, make sure you’re well-versed in the latest data quality frameworks and tools. Familiarise yourself with how these frameworks can be applied in a federated model, as this will show your understanding of the role's requirements.
✨Showcase Your Collaboration Skills
This role is all about collaboration across various teams. Prepare examples from your past experiences where you successfully worked with engineering, governance, or business teams to implement data quality solutions. Highlight your ability to bridge gaps between technical and business needs.
✨Prepare for Scenario-Based Questions
Expect scenario-based questions that assess your problem-solving skills in complex data quality issues. Think through potential challenges you might face in this role and how you would approach them, demonstrating your strategic thinking and technical awareness.
✨Communicate Clearly and Effectively
Since documentation and communication are key aspects of this role, practice articulating your thoughts clearly. Be ready to discuss how you maintain records of designs and decisions, and how you communicate progress to stakeholders at all levels.
