Enterprise Data Steward | Permanent | Hybrid (Johannesburg northern suburbs)
Job purpose
The Data Steward is a data governance role within the company that is responsible for ensuring the quality and fitness for purpose of the organisation's data assets, including the metadata for those data assets. To provide data management services for the client data domain that spans more than one cluster. Ensure a complete view of client data throughout the organisation and inform and implement the decisions of the data governance council.
Job responsibilities
Provide data management services for the business area Data domain and Enterprise Data Warehouse that spans more than one cluster. Coordinate with clusters to ensure complete view of data in the data warehouse throughout the organisation and inform and implement the decisions of the data governance council.
Provide strategic oversight and ensure governance controls are in place to appropriately govern processes within the business area and data warehousing ecosystem. Actively collaborate with stakeholders to maintain alignment of the Company’s data practices to industry, mature the practice and entrench within the operations of the organisation.
Maintain up to date knowledge of latest developments in data ecosystem, carry out research and consult industry experts regarding best practice, regulation, and technology trends, build external networks that facilitate deeper understanding, attend relevant forums.
Engage with stakeholders to obtain an understanding of their data warehousing needs. Become a trusted advisor to, and influence decision making of stakeholders by providing an advisory service, guidance and support on data policies, management practices, processes, training requirements etc.
Identify opportunities to influence the improvement or enhancement of business processes and methodologies by researching and recommending improvement initiatives and effective ways to operate and add value to Nedbank.
Provide strategic input into the Enterprise Data Strategy on Management and Governance of data in the data warehousing environment to create alignment and to leverage opportunities for data reuse.
The implementation of Data Governance policies while executing data management services on projects or daily business operations in all the business area domains and Data Warehousing Environment.
Contributing to the development of standards for data within the data business area domains in alignment with the company and provide oversight and assurance on adherence to governance standards.
Documenting and communicating the rules and standards around the data in all company technology domains.
Defining data quality rules and business meta data in collaboration with the source data owners for all data elements loaded to the company Data Reservoir
The translation of business defined data quality rules to technical data quality rules which will be executed when data is loaded to the company Data Reservoir
The refinement of data quality rules based on data consumer requirements which initiates data quality remediation efforts in collaboration with data source owners in the business area.
Ongoing monitoring and resolution of data quality issues pertaining to data in the business area domains.
Validating automated data lineage and mapping of data lineage manually.
Establishing and maintaining collaborative partnerships with data owners in the business area and data consumers, represented by various Clusters in the company (Exco, Manco, and Regulatory Reporting).
Evaluating business requirements and acts as liaison between data owner and data consumers to ensure business value is derived.
Qualification requirements
Advanced Diplomas/National 1st Degrees
Data Management (DAMA) Certification, Certification/formal training in relevant technology
Essential certifications
DAMA-certified data management professional (CDMP) or similar data management certification
Minimum experience level
5-7 years’ experience is in a data management /business role.
High-level Understand BCBS239/RDARR, POPIA, GDPR and another relevant regulatory knowledge.
DAMA
Technical knowledge
Ab Initio stack
Metadata Hub (implementation of lineage, data glossary)
ExpressIT (capturing data quality rules, testing, profiling, implement rules)
Data analysis Basic concepts
Write and read SQL code
Professional knowledge
Company policies and procedures
Relevant regulatory, compliance and risk legislation
Industry trends
Business Acumen
Relevant software and systems knowledge
Banking knowledge
Research methodology
Principles of financial management
Governance, risk and controls
Operational risk management
Behavioural competencies
Adaptability
Building Partnerships
Communication
Decision Making
Stress Tolerance
Technical/Professional Knowledge and Skills
Technical knowledge
Ab Initio stack
Metadata Hub (implementation of lineage, data glossary)
ExpressIT (capturing data quality rules, testing, profiling, implement rules)