Your area of work:
As part of the newly established team, you will work on the roll-out of the data governance program across multiple business segments and streams, providing support to businesses during the transformation and, subsequently, maintenance phases. The role foresees taking the lead of one of the workstreams, eventually transitioning into the main point of contact for the stream-related content within Clearstream Data Governance Office.
Your responsibilities:
- Support definition and development of Data quality framework, respective policies, standards, and procedures.
- Collaborate with business areas, IT counterparts and other relevant functions to conduct data quality assessments, including review, initial conceptualisation and prototyping of data quality KPIs.
- Support business requirement definition on enterprise Data Quality Monitoring solutions and KPIs, to ensure consistency across prioritized business areas and data domains.
- Collaborate with relevant Data governance and Management stakeholders on the implementation of data quality monitoring tools to systematically measure and monitor the quality of the data. Support business areas in the operationalization of the solutions and transition to BAU.
- Collaborate with relevant DMG stakeholders to facilitate resolution of data quality issues and further improvements.
- Report on the workstream progress to senior management and DMG stakeholders, as required.
- Create, review, and maintain relevant documentation.
- Support DMG related impact assessments and queries.
- Develop and maintain effective relationships with internal stakeholders and other DMG relevant actors, to ensure good organizational alignment.
Your profile:
- Educational background in a quantitative discipline (Quantitative Finance, Statistics, Computer Science, Engineering or alike).
- At least 7 years of proven track record in quantitative roles (data/ business analyst/ model developer focusing on data governance, data quality and/or data analytics etc.).
- Sound understanding of data quality dimensions and data quality steering in enterprise-wide context.
- Good understanding of financial markets and products, familiarity with post-trade business and Financial Market Infrastructures is an advantage.
- Sound knowledge of statistics and econometric methods and their application.
- Proven experience in solutions conceptualization and prototyping, fluency in Python/R/SQL or alike. Familiarity with enterprise-grade data quality solutions is an advantage.
- Attention to detail, strong analytical and problem-solving skills, ability to draw accurate conclusions based on complex data.
- High commitment, team spirit, excellent communication, and interpersonal skills.
- Excellent command of written and spoken English. German and/or French will be an asset.