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- Tasks: Lead the charge in enhancing data quality across the organisation with innovative frameworks and tools.
- Company: Join a forward-thinking company dedicated to data excellence and collaboration.
- Benefits: Enjoy competitive pay, flexible working options, and opportunities for professional growth.
- Why this job: Make a real impact on how data quality is managed and operationalised at scale.
- Qualifications: Strong understanding of data quality principles and excellent collaboration skills required.
- Other info: Be part of a dynamic team focused on strategic enablement and continuous improvement.
The predicted salary is between 36000 - 60000 £ per year.
The Data Quality Lead role is central to building the foundations for enterprise-wide federated Data Quality. Reporting directly to the Data Quality Manager, you will work closely with the Global Head of Data Quality and other senior leaders within the Chief Data Office (CDO) team 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 both 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 data quality team is distinct from the BAU team, which owns day-to-day management and resolution of DQ issues. The data quality 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 both 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 in London employer: Howden
Contact Detail:
Howden Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Quality Lead in London
✨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 data quality initiatives. Show them you’re not just another candidate; you’re genuinely interested in their mission and how you can contribute.
✨Tip Number 3
Practice your pitch! Be ready to explain how your skills align with their needs, especially around data quality frameworks and collaboration. Confidence is key!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who take that extra step.
We think you need these skills to ace Data Quality Lead in London
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 Technical Know-How: Don’t shy away from mentioning your technical skills! Whether it’s metadata models or profiling mechanisms, let us know how you can contribute to making data quality actionable and scalable.
Communicate Clearly: We love clear communication! Ensure your application is well-structured and free of jargon. This will help us understand your thought process and how you can bring clarity to ambiguity in the role.
Apply Through Our Website: For the best chance of success, make sure to apply directly through our website. It’s the easiest way for us to keep track of your application and get back to you quickly!
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 frameworks and tools related to data quality. Familiarise yourself with concepts like rulebooks, metadata models, and profiling mechanisms. This will not only show your technical awareness but also demonstrate your ability to translate strategic objectives into actionable plans.
✨Showcase Your Collaborative Spirit
This role is all about collaboration, so be prepared to discuss your experience working with cross-functional teams. Share specific examples of how you've engaged with engineering, governance, or business teams to implement data quality standards. Highlighting your ability to bridge business requirements and technical implementation will set you apart.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving skills in complex data quality scenarios. Think of past experiences where you had to act as a point of escalation or provide third-line support. Be ready to explain your thought process and how you ensured consistency in applying data quality standards.
✨Communicate Clearly and Effectively
Since documentation and communication are key aspects of this role, practice articulating your thoughts clearly. Prepare to discuss how you maintain records of designs and decisions, and how you communicate progress to stakeholders. Strong communication skills will be crucial in demonstrating your fit for this collaborative position.
