Data Quality Analyst

Catalog:

•Setup and manage our data catalog using Microsoft Purview, including classification, search, and integration with data sources.

•Catalog datasets as priortised collecting metadata such as source, type, format, size, quality, lineage, and tranformations etc.

•Implement data classification for datasets based on sensitivity, confidentiality, and regulatory requirements.

•Configure the tool to support easy search and discovery of datasets and metadata.

•Advise on the management of data lifecycle for our systems including data retention

Analyse & Report:

•Analyse datasets for data quality to identify inconsistencies, errors, and data quality issues.

•Perform data profiling activities to increase knowledge on quality of critical datasets.

•Develop and implement data quality standards, processes, and procedures.

•Arrange development of data quality reporting to be available to Data Owners / Stewards for critical datasets.

•Monitor and report on data quality metrics and trends.

Engage:

•Collaborate with various teams to understand data requirements and ensure data quality goals are met.

•Identify opportunities for process improvements and automation to enhance data quality, and engage colleagues to drive these initiatives.

•Provide guidance and support to stakeholders on data quality best practices.

•Stay updated with industry trends and emerging technologies related to data quality.

Qualifications and/or Experience

•Proven experience working as a Data Quality Analyst in a large enterprise.

•Desirable: Degree in Computer Science, Information Management or related field.

•Experience with use of Microsoft Purview, and use of Data Cataloging tools.

•Familiarity with data quality tools and technologies.

•Strong knowledge of data quality principles, practices, and methodologies.

•Proficient in SQL and data manipulation languages.

•Experience with data profiling and data cleansing techniques.

•Understanding of data governance principles and frameworks.

•Prior experience working in Agile teams.

•Knowledge of relevant data protection regulations and compliance requirements, such as GDPR.

Individual competencies

•Analytical Thinking: Proficient in analysing complex data sets and identifying patterns, trends, and anomalies.

•Attention to Detail: Ability to identify and rectify data quality issues with precision and accuracy.

•Problem Solving: Capability to identify root causes of data quality issues and develop effective solutions.

•Collaboration: Aptitude to work effectively with cross-functional teams and stakeholders to achieve data quality goals.

•Continuous Learning: Willingness to stay updated with industry best practices and emerging technologies in data quality.

•Communication: Strong verbal and written communication skills to convey complex ideas and concepts to technical and non-technical audiences.

•Influence: Ability to influence others to adju...