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Permanent

Data Quality Analyst

London
money-bag Negotiable
27C0B12216193D145A24237BA618D340
Posted 3 days ago

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.

Is this your next job Read the full description below to find out, and do not hesitate to make an application.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 frameworkHelp create, implement, and maintain data governance policies and procedures to ensure the business is compliant with relevant regulatory requirementsWork with data owners and data stewards to establish and enforce data quality metrics, monitoring, and improvement processesIdentify and appoint data stewards, providing guidance and supportDevelop and maintain a data catalog, taxonomy, and data lineage documentationAdvocate for data quality best practices and drive initiatives to enhance data-driven decision-makingDevelop and deliver training and awareness programs to promote data governance and data quality principles across the organizationExperience Required:Minimum of 3 years in data governance, data management, or a related fieldData Governance Expertise: Proven experience in developing and implementing data governance/quality policies and procedures in a regulated environmentTechnology Skills: Familiarity with data management technologies and tools, such as data catalogues, data lineage, and data quality toolsStakeholder 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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