Senior Data Management Analyst at Old Mutual

Job Purpose

Ensure that data and information resources are managed as a strategic asset by using and applying appropriate statistical tools, data management methodologies and processes that produce consistent, reliable and accessible data, information and insight to achieve OMI’s business goals.

Job Objective

Perform Data Management activities that will increase the value of company data:

 Data Management Planning

• Identify data needs which are based on the company business strategic objectives, measures, targets and initiatives, and the required analysis in support of decision making
• Establish whether the existing data availability, accessibility and quality is meeting the business needs and develop data strategies to close the gap
• Research and explore new ways to find and collect relevant data from potential new sources of information
• Analyse business information with the objective to reduce data process related costs and increase productivity of data availability and accessibility to the users
• Estimate Data Asset value & associated Data Management costs
• Communicate & promote the value of Data Assets
• Participate in the development and review of Data Policies, Standards and Procedures
• Managing and designing the reporting environment for data sources, quality, security and metadata
• Supporting initiatives for data integrity and normalisation

Meta Data Management

• Understand Meta Data Requirements and align specification to the appropriate maturity level
• Develop & maintain business Meta Data and the Meta Data standards
• Manage metadata repositories (directories, glossaries and other metadata stores)
• Support business Meta Data reporting and analysis
• Collaborate with business users and analytics team to determine dimensional hierarchies and provide specification to IT for the ongoing maintenance thereof
• Develop and maintain data specification for various uses:
• Reporting, management dashboards & scorecards
• Conduct data related due diligence process for third party systems, intermediaries and binder holders
• Data integration with other external data sources

Data Quality Management

• Establish data quality expectations and define requirements from business users
• Test and validate data quality requirements
• Develop data quality standards, methodologies, algorithms, processes and guidelines
• Design and implement operational data quality management procedures
• Monitor operational data quality management procedures & performance
• Define and document data quality requirements & business rules
• Develop and promote data quality awareness
• Define data quality metrics and service levels
• Manage Service Level Agreements for data quality with internal and external suppliers
• Embed data quality certification scores in the fact tables
• Provide quality assurance of imported data
• Profile, measure, analyse and assess data quality
• Perform data quality root cause analysis
• Analyse the impact of data quality to business decision making
• Continuously measure, monitor and report data quality
• Establish and manage data quality certification reporting
• Assist in managing and resolving data related issues as experienced by Data Owners, Stewards and Custodians and present possible solutions to the Data Governance Council
• Propose solutions to correct data quality defects
• Assist in the prioritization initiatives for data management by conducting an analysis of the costs vs benefits using statistical methods
• Provide support to Data Management audit activities
• onitor conformance with Data Policies, Standards and Architecture
• Identify potential risks to the security of data and assist to find solutions to ensure data system integrity
• Assist in establishing data security guidelines
• Apply data security guidelines to the data
• Review business security rules and data access views
• Adhere to data security controls
• Assist with data security classification
• Develop metrics for data management
• Produce data management reports that highlight trends and provide recommendations for the improvements

 Identify, develop and/or apply data management analysis tools and techniques and actively participate in analytics team's knowledge and capability development.

• Testing statistical differences
• Looking for unknown data relationships
• Use of graphical tools to help visualize relationships between variables
• Use of statistical packages to perform data quality tests
• Data risk modeling tool
• Data profiling
• Six Sigma
• Data management reporting tools

Minimum Requirements

• Minimum Bachelor’s degree in Computer Science,  Informatics, Engineering, Mathematics, or Operations Research
• 3 – 5 years’ experience in building data marts, data models, knowledge in applying fundamental data transformation, cleaning, validation and statistical techniques, and data quality analysis
• Quantitative problem-solving skills
• Ability to work effectively with people at all levels in an organisation
• Ability to communicate complex ideas effectively both verbally and in writing (English)
• Knowledge of SQL, BI Platforms, Excel-VBA/Access, SAS, SharePoint
•  Knowledge of R, PYTHON and HADOOP is advantageous.

Shortlisted candidates will be subjected to the following statutory checks:

• ITC
• Criminal
• References
• Qualifications