Oliver James is looking for a Data Steward Senior for different roles, with strong capabilities.
We introduce talented people to great organisations so that both may grow and benefit from each other's experiences, helping to fulfil their potential. As such, you can come to expect a consistently high level of service and delivery, placing up to C-suite talent in permanent and contract positions, as well as project-based consultancy and temp solutions worldwide from our 12 global locations.
The Senior Data Steward will lead strategic data management initiatives, ensuring the quality, integrity, and compliance of organisational data assets. Responsibilities include data governance, quality management, meta data oversight, and collaboration with cross-functional teams.
- Develop and enforce data governance policies, ensuring compliance with industry regulations.
- Collaborate on frameworks for data classification, ownership, and life cycle management.
Data Quality Management:
- Define and enforce data quality standards, implementing monitoring processes.
- Collaborate with business units to establish and monitor data quality metrics.
Meta data Management:
- Oversee meta data repositories, ensuring comprehensive documentation of data assets.
- Facilitate development of meta data standards and taxonomies.
Project: Data Transparency and GDPR:
- Lead projects promoting data transparency initiatives.
- Ensure compliance with GDPR regulations, collaborating with Information Security.
Collaboration and Communication:
- Work closely with stakeholders to understand data requirements and challenges.
- Contribute to the development of data-related training programs.
- Master's degree in relevant field.
- 5 Years of proven experience in data stewardship or related roles.
- Strong understanding of data governance, quality, and meta data management.
- Familiarity with GDPR and data privacy regulations.
- Excellent communication and collaboration skills.
- Experience with data management tools (Collibra, Informatica,…).
- Certification in data management (e.g., CDMP, DAMA).