Data Quality & Automation Analyst

Data Quality & Automation Analyst

Full-Time 30000 - 40000 £ / year (est.) No working from home possible
LexisNexis Risk Solutions

At a Glance

  • Tasks: Build and maintain high-quality data for sales compensation while improving automation.
  • Company: Join RELX, a leader in data operations with a focus on innovation.
  • Benefits: Enjoy competitive pay, flexible working options, and opportunities for growth.
  • Other info: Collaborative environment with strong support from Sales, Finance, and tech teams.
  • Why this job: Make a real impact by ensuring data accuracy and enhancing stakeholder confidence.
  • Qualifications: Experience in data operations and a knack for automation.

The predicted salary is between 30000 - 40000 £ per year.

RELX is seeking a data operations specialist to build, validate, and maintain high‑quality participant‑level data underpinning sales compensation outcomes.

You will collaborate with Sales Operations, Finance and tech partners to ensure data accuracy, auditable trails, and readiness for payout cycles.

The role emphasizes improving automation, reducing manual effort, and strengthening stakeholder confidence in compensation data across the organisation.

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Data Quality & Automation Analyst employer: LexisNexis Risk Solutions

At ICIS, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters collaboration and accountability. Our commitment to employee well-being is reflected in our generous benefits package, extensive learning opportunities, and a supportive environment that encourages personal and professional growth. Join us in our mission to optimize the world's resources while enjoying a fulfilling career in a globally distributed team that values your insights and contributions.

LexisNexis Risk Solutions

Contact Details:

LexisNexis Risk Solutions Recruitment Team

We think you need these skills to ace Data Quality & Automation Analyst

Data Operations
Data Validation
Data Maintenance
Sales Compensation Analysis
Collaboration
Data Accuracy
Auditable Trails