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Data Quality Analyst

Hanson Lee
London
4 weeks ago
Applications closed

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Data Quality Consultant

A successful and established London Market syndicate is seeking a highly motivated and detail-oriented Data Quality Analyst to join their team. The Data Quality Analyst is integral to ensuring the organization's data assets are managed, secured, and utilized to support business decision-making.


As Data Quality Analyst will play a key role in maintaining and driving quality standards, policies, and procedures related to data governance while collaborating with stakeholders across departments to enhance data quality and integrity.


NB: If you do not have experience of working in the insurance sector, you will unfortunately NOT be eligible for this role.


Key Responsibilities:

  • Develop and implement a comprehensive data governance framework
  • Help create, implement, and maintain data governance policies and procedures to ensure the business is compliant with relevant regulatory requirements
  • Work with data owners and data stewards to establish and enforce data quality metrics, monitoring, and improvement processes
  • Identify and appoint data stewards, providing guidance and support
  • Develop and maintain a data catalog, taxonomy, and data lineage documentation
  • Advocate for data quality best practices and drive initiatives to enhance data-driven decision-making
  • Develop and deliver training and awareness programs to promote data governance & data quality principles across the organization


Experience Required:

  • Minimum of 3 years in data governance, data management, or a related field
  • Data Governance Expertise: Proven experience in developing and implementing data governance/quality policies and procedures in a regulated environment
  • Technology Skills: Familiarity with data management technologies and tools, such as data catalogues, data lineage, and data quality tools
  • Stakeholder Management: Proven history of working with both technical and non-technical stakeholders, bridging the gap between data teams and business units

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