The Data Quality Analyst provides expertise in the analysis, monitoring and improvement of data quality to ensure data complies with established business rules and is fit for purpose. This role examines complex data issues and will work with Data Producers, Data Stewards and other key stakeholders to determine the root causes of data quality problems, to develop appropriate business data quality rules, and in time implement and enforce them in applications and platforms. The role will also assist stakeholders to monitor and report on data quality via business-facing data quality dashboards.

Your main responsibilities

Validate the data quality framework and develop an approach to Data Quality that balanced cost vs benefit.

Provide expertise on Data quality processes, metrics and tooling in a federated DQ environment.

Leverage the roles and responsibilities, councils and working groups to facilitate input and remediation on Data Quality

Perform data profiling on datasets to determine baseline data quality and integrity;

Proficiency in the configuration/development of rule sets including; data cleansing, parsing, standardization, validation, data quality exception monitoring/handling, etc;

Collaborating with data architects, business application developers and data engineers to improve data collection and storage processes;

Work with data stewards for root cause analysis and data remediation plans as needed;

Reporting data analysis findings via dashboards and/or reports to monitor compliance and track resolution of data issues;

Adhere to industry best practices in data analysis and collection.

These are the competencies that suit you

Competent with performing data profiling and analysis using both commercial data profiling / data quality tools or via SQL queries or other approaches;

Working with large and often complex data sets, strong analytical skills and the ability to evaluate and interpret trends and important information

Root cause analysis, cost-benefit analysis and ROI discovery

Data visualization and reporting skills (e.g. Power BI, Tableau, etc.)

Knowledge of SQL, Python, and other database scripting techniques

Understanding of data governance principle and practices and how these relate to data quality improvement

The skills you bring

Solid teamwork with interpersonal skills

Good communication skills, also with presenting to (senior) stakeholders;

Ability to influence and convince;

You bring initiative and creativity and you are a critical thinker;

You take accountability for your work and you are a reliable business partner;

Problem solving is a key skill you bring along;

You are action-oriented and an easy self-starter.

Preferred Qualifications:

At least a Bachelor’s degree in a relevant subject – preferred not essential;

5+ years’ of relevant working experience in Data Quality within an IT environment;

Preferably experience within a corporate working environment;

Experience with working in the financial industry is a plus.

What will you be getting?

You will be earning a competitive salary based on 40 hours and your education, knowledge and experience;

You will also receive a thirteenth month and a holiday allowance in the form of a monthly flex budget, amounting to 16.7% of your monthly salary;

Plenty of scope and budget for your personal development;

A minimum of 27 holiday days;

Reimbursement of your travel expenses;

A good pension scheme.

Interested? Apply!
Are you interested in joining our CDO office? We look forward to receiving your resume and motivation letter. Then make sure you apply immediately! Do you have some more questions? Send an email to our Talent Acquisition Specialist Max Krajenbrink at

Diversity & Inclusion

At Aegon Asset Management, we are committed to fostering a diverse workforce and an inclusive culture. We are more than a global Asset Management firm – we are a people business, and we recognize that delivering excellent client outcomes comes from harnessing diverse perspectives. We value diversity in the full range of human uniqueness without limitation including race, gender, ability, language, culture, beliefs, age, origin, background, perspectives and experiences.

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