At a Glance
- Tasks: Lead data quality issue resolution and guide offshore analysts to ensure accuracy.
- Company: Join a collaborative and innovative company that empowers progress.
- Benefits: Competitive salary, professional development, and a supportive work environment.
- Other info: Great opportunity for career growth and to work with talented colleagues.
- Why this job: Make a real impact by solving complex data challenges in the insurance sector.
- Qualifications: 5+ years in data quality or analysis, strong analytical and communication skills.
The predicted salary is between 36000 - 60000 £ per year.
With a company culture rooted in collaboration, expertise and innovation, we aim to promote progress and inspire our clients, employees, investors and communities to achieve their greatest potential. Our work is the catalyst that helps others achieve their goals. In short, We Enable Possibility℠.
Key Tasks and Responsibilities
- End to End Ownership of the Data Quality Issue Lifecycle: Oversee triage, root‑cause analysis, assignment, resolution, and closure of data issues. Ensure SLAs are met, blockers escalated, and stakeholders updated. Maintain a clear and transparent view of issue status and ageing.
- Lead and guide offshore Data Quality Analysts: Provide daily direction, prioritisation, and quality oversight. Review offshore work outputs to ensure accuracy and consistency. Coach analysts to improve investigation quality, documentation clarity, and prevention thinking.
- Work directly with stakeholders across the business: Act as the primary point of contact for UK‑based data owners, SMEs, and operations teams. Run workshops or playback sessions to explain issues, remediation plans, and expected changes. Translate technical findings into clear business terms.
- Partner with IT and Operations to deliver fixes: Collaborate with technology teams to validate technical defects and ensure production fixes are implemented correctly. Align with Operations to embed new processes that prevent recurrence. Support change assessments where fixes intersect with projects or system releases.
- Drive structural data quality improvements: Identify recurring issue patterns and propose prevent‑rather‑than‑correct actions. Contribute to data rule definitions, quality controls, validation logic, and monitoring dashboards. Recommend updates to data standards, lineage, and ownership models.
- Reporting and governance: Produce weekly/monthly DQ reporting for management. Ensure all issues are documented to an audit‑ready standard. Support Data Governance forums with insights on emerging risks and thematic trends.
Skills / Competencies
- Deep understanding of critical data flows and business processes within the speciality insurance market including the London Market.
- Ability to produce clear and concise reports and documentation for both technical and non-technical audiences.
- Strong analytical mindset with proven ability to diagnose complex data issues.
- Excellent communication skills — able to simplify technical topics for business colleagues.
- Stakeholder confidence: comfortable leading conversations and challenging assumptions constructively.
- Organised and structured, with the ability to manage multiple concurrent issues.
- Skilled in root‑cause analysis methods (e.g., 5 Whys, Fishbone, data lineage mapping).
- Ability to guide offshore teams and ensure consistent quality of work.
- Understanding of data governance, data controls, and regulatory data expectations.
- Proficiency with SQL, Excel, and data quality tooling (DQ dashboards, issue‑tracking, profiling tools).
Qualifications
- Bachelor’s or master’s degree in a highly analytical discipline.
- Nice to Have: Professional certifications in business analysis (e.g. ISEB) and data management (e.g. DAMA).
Experience
- 5+ years in data quality, data analysis, MDM, or similar roles.
- Experience leading or mentoring junior or offshore analysts.
- Demonstrable success resolving cross functional data issues end to end.
- Experience within specialty insurance and the London Market.
- Exposure to root cause analysis, issue management tooling, and data governance practices.
Do you like solving complex business problems, working with talented colleagues and have an innovative mindset? Arch may be a great fit for you. If this job isn’t the right fit but you’re interested in working for Arch, create a job alert! Simply create an account and opt in to receive emails when we have job openings that meet your criteria. Join our talent community to share your preferences directly with Arch’s Talent Acquisition team.
Data Quality Lead - Issue Resolution employer: Arch
Arch is an exceptional employer that fosters a dynamic work culture in Greater London, where innovation and collaboration thrive. Employees benefit from comprehensive growth opportunities, including professional development and leadership training, all while contributing to impactful transformation strategies. Join us to be part of a team that values your expertise and empowers you to make a meaningful difference.
StudySmarter Expert Advice🤫
We think this is how you could land Data Quality Lead - Issue Resolution
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, especially those who work at companies you're interested in. A friendly chat can lead to insider info about job openings and even referrals.
✨Tip Number 2
Prepare for interviews by practising common questions and scenarios related to data quality and issue resolution. We recommend doing mock interviews with friends or using online platforms to get comfortable with articulating your experience.
✨Tip Number 3
Showcase your analytical skills during interviews. Be ready to discuss specific examples of how you've tackled complex data issues in the past. This will demonstrate your problem-solving abilities and make you stand out.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, you can set up job alerts to stay updated on new openings that match your skills.
We think you need these skills to ace Data Quality Lead - Issue Resolution
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter to highlight your experience in data quality and issue resolution. We want to see how your skills align with the key tasks and responsibilities outlined in the job description.
Showcase Your Analytical Skills:Since this role requires a strong analytical mindset, don’t shy away from sharing specific examples of how you've diagnosed complex data issues in the past. We love seeing real-life applications of your skills!
Communicate Clearly:Remember, you’ll need to simplify technical topics for non-technical audiences. Use clear and concise language in your application to demonstrate your communication skills. We appreciate clarity just as much as you do!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy to do!
How to prepare for a job interview at Arch
✨Know Your Data Inside Out
Before the interview, dive deep into the data quality issues relevant to the specialty insurance market. Familiarise yourself with common problems and solutions, as well as the tools used in data governance. This will help you speak confidently about your experience and how you can contribute to resolving complex data issues.
✨Showcase Your Leadership Skills
Be prepared to discuss your experience leading teams, especially offshore analysts. Share specific examples of how you've guided teams through challenges, prioritised tasks, and ensured quality outputs. Highlight your coaching methods and how you’ve improved team performance in past roles.
✨Communicate Clearly and Effectively
Practice simplifying technical jargon into business-friendly language. During the interview, demonstrate your ability to communicate complex data findings clearly to non-technical stakeholders. This skill is crucial for the role, so think of examples where you successfully translated technical issues into actionable insights.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving skills, such as how you would handle a recurring data issue. Prepare structured responses using root-cause analysis methods like the 5 Whys or Fishbone diagram. This will show your analytical mindset and your ability to drive structural improvements in data quality.
