Job Summary
Our Client a global tech firm is seeking a Senior Data Analyst to join their team in Sandton on a contract basis. The offer stability, growth and excellent remuneration package.
Purpose
To assist us in capturing processes and data lineage, being supported and led by a senior Data Management
Requirements
- Data Management and Governance
- Metadata
- Ref Data
- Data Quality
- Data Analyst / Process Engineer
Data Management and Governance:
- Establish and govern an enterprise data governance implementation roadmap including strategic priorities for development of information-based capabilities
- Roll out an enterprise-wide data governance framework, with a focus on improvement of data quality and the protection of sensitive data through modifications to organization behavior policies and standards, principles, governance metrics, processes, related tools and data architecture
- Define roles and responsibilities related to data governance and ensure clear accountability for stewardship of the company’s principal information assets
- Serve as a liaison between Business and Functional areas and technology to ensure that data related business requirements for protecting sensitive data are clearly defined, communicated and well understood and considered as part of operational prioritization and planning
- Develop & maintain inventory of the enterprise information maps, including authoritative systems, owners
- Facilitate the development and implementation of data quality standards, data protection standards and adoption requirements across the enterprise
- Define indicators of performance and quality metrics and ensure compliance with data related policies, standards, roles and responsibilities, and adoption requirements
- Lead Senior Management, comprising resources from the Business and Functional areas and IT business and operations functions, to achieve their objectives; resolve issues escalated from Business and Functional areas data governance representatives
- In conjunction with the IT, provide progress reports to management and oversee periodic updates to the Data Governance Roadmap
- Coordinate external data sources to eliminate redundancy and streamline the expense related to those services
- Identify new business opportunities pertaining to the use of information assets to achieve efficiency and effectiveness in the marketplace / represent data as a strategic business asset at the Senior Management table
Metadata:
- Metadata Data Manager will develop data integration solutions focused on the development of the Enterprise Data Warehouse. The role is responsible for managing the development of and maintenance of business metadata (business information about the data such as field definitions, business rules and appropriate use) related to data used by the enterprise to conduct business and resolution of issues related to Metadata/Reference Data. Manages the proper use of data, determines appropriate security and access rights and determines requirements for data quality, maintenance and distribution.
- Additional tasks may include data analysis, conversion and Extract, Transform, Load (ETL) specifications, implementation planning and coordination (for metadata), and implementation or other support. Independent development maintenance, and compliance monitoring of the agency's written metadata and reference data management standard including but not limited to policy, procedures and training Participate in defining appropriate metrics to measure the quality of the metadata and reference data being used. Develops process for capturing and maintaining metadata from all data warehousing components.
- Develop data maintenance and governance processes and procedures, to obtain and maintain accurate master data. Define process, frequency and responsibility for identification of metadata or reference data discrepancies and resolution.
References Data Management:
- Develop and maintain metadata and reference data related to data used by the enterprise to conduct business.
- Serve as business process expert for one or more datasets (i. e. Set of data elements collected for one program or purpose and is the central contact point for information about the origins and revisions to those data elements; responsible for the accuracy of the data in these elements, both within operational applications and in downstream data warehouses and reports.
- Create a well-documented, end-to-end information blueprint tracing business requirements with enterprise and reference data.
- Establish a common business language and manage business perspectives about information, aligning those views with the IT perspective.
- Manage and explore data lineage to create trusted information that supports data governance and compliance efforts.
- Ensures the accuracy of metadata and reference data in association with business/technical required policy and procedures. Explores data lineage and creates trusted information that supports data governance and compliance efforts.
- Ensures the accuracy of metadata and reference data in association with business/technical required policy and procedures. Identifies and assesses potential issues in business/technical definitions.
Data Quality:
- Build and maintain data quality rule libraries to support and manage enterprise data quality initiatives
- Leverage ETL tools (BODS/Informatica) to extract and stage data from ERP and Legacy
- Enhance global data quality toolset to support continuous data quality improvement processes
- Collaborate with functional team members to understand requirements and propose solutions
- Execute data profiling and provide insights in partnership with functional team members to determine health of data quality
- Responsible for development of technical specifications and related test scripts
- Responsible for release management
- Responsible for solution documentation
- Develop related to quality scorecard/report capabilities
- Develop data quality reports to manage quality between SAP & Legacy Systems
- Provide ad-hoc data quality analysis and support
Data Analyst / Process Engineer:
- Data engineers are responsible for finding trends in data sets and developing algorithms to help make raw data more useful to the enterprise. This role requires significant set of technical skills, including a deep knowledge of SQL database design and multiple programming languages, but also need communication skills to work across departments to understand what business leaders want to gain from the company’s large datasets. The data engineer will be tasked with managing and organizing data, while also keeping an eye out for trends or inconsistencies that will impact business goals. It’s a highly technical position, requiring experience and skills in areas like programming, mathematics and computer science, but data engineers also need soft skills to communicate data trends to others in the organization and to help the business make use of the data it collects.
Some of the most common responsibilities for a data engineer include:
- Develop, construct, test and maintain architectures
- Align architecture with business requirements
- Data acquisition / sourcing
- Develop data set processes
- Use programming language and tools
- Identify ways to improve data reliability, efficiency and quality
- Conduct research for industry and business questions
- Use large data sets to address business issues
- Deploy sophisticated analytics programs, machine learning and statistical methods
- Prepare data for predictive and prescriptive modelling
- Find hidden patterns using data
- Use data to discover tasks that can be automated
- Deliver updates to stakeholders based on analytics
