Data Steward

2 weeks ago

Johannesburg, South Africa FirstRand Full time

About us, purpose, experience and qualifications

**about us**:
**purpose**:

- The Data Steward is responsible for the execution of the strategy and business processes required to create, maintain, and enhance RMB’s data. The position is ultimately responsible for data cleansing, data definitions, process documentation, as well as serving in a consultant role to functional teams providing best practices, improved processes and architecture, data interpretation and training. The Data Steward is also typically the “go to” person within a specific domain for all the queries/issues related to data.**experience and qualifications**:

- Bachelor’s Degree required
- 3-5 years of experience in managing financial data - data vendor on-boarding, data quality management rules and alerts configuration, exception resolution, master data management principles including implementation, data migration activities etc.
- Advanced data analysis skills using Excel, SQL and reporting tools to import, analyse and report on data
- Experience
- Expertise in specific Financial Services domains, including expertise at the intersection of risk, finance, employee customer and counterparty domains;
- Sound knowledge of data management life-cycle and data governance principles
- Sound knowledge of data architecture
- Sound knowledge of metadata, master data, data integration principles and data quality management
- Sound SQL knowledge
- Familiarity with reporting tools such as Microsoft Reporting Services and OBIEE
- Data modelling skills
- Expertise in business and IT architecture, including familiarity with leading architectural standards such as TOGAF, FEA and/or Zachman;
- Familiarity with Enterprise Metadata Management (business and IT) and OMG standards;
- Information management program life cycle experience;
- Experience in operationalizing Data Governance, Data Stewardship and Data Quality;
- Expertise in creating and deploying best practices and methodologies;
- Familiarity with industry data models such as IBM BDW and IIW, Teradata FSLDM, and SAS IIA;
- Familiarity with software development lifecycles;
- Familiarity with process modelling, semantic modelling and data modelling.

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