Senior Data Analyst

Who are we?
The Sanlam Retail Affluent business (SRA) is dedicated to empower South Africans in the middle
- and upper-income segments to be financially confident, secure and prosperous. With deep client understanding and a focus on excellence in technology, client and intermediary experiences, SRA delivers financial solutions including comprehensive financial planning, life
- and disability insurance, credit solutions, savings and investments, retirement and fiduciary services that can be accessed through various platforms. Role Description
Sanlam Business Intelligence (SBI) is a centre of excellence that delivers data and analytical services within the Sanlam Life and Savings (SLS) cluster. SLS provides clients across different market segments (entry-level, middle-income, affluent, professional market and business owners) with a comprehensive range of appropriate and competitive financial solutions.
These include traditional life insurance risk and savings products, investment, retirement, health and fiduciary services. Designed to facilitate long-term wealth creation, protection and niche financing, these solutions are engineered around client needs.
Are you analytically minded, curious and enthusiastic about data? Passionate about finding insights in datasets, with the ability to synthesise and clearly communicate the results and drive business impact?
An exciting opportunity exists in the SBI Scalable Warehouse Team.
We are looking for an individual with experience in data analysis, data modelling and with a keen passion to build data warehouses.
If you believe you have what it takes, then come join the team and assist us to mature our data warehousing capability as you grow your skills and competencies in this exciting field.
You will be responsible for the end-to-end tasks within the data analysis framework working with business representatives, product owners, etc. to define and elicit requirements, analyse data and own the enterprise data warehouse model. What will you do? Key result areas

Data Modelling
Define standards and guidelines for various delivery teams to adopt and build out domain specific data models
Drive adoption of the enterprise data modelling tool as the central repository of the enterprise vault layer
Provide SME guidance and act as coach/ mentor to help workload teams adopt and implement the Data Vault Modelling Technique (DV).
Chair the Data Vault Analyst Forums to drive alignment of Shared Hubs and consistency across Links and Satellites

Enterprise Vault Layer
Collate information from various stakeholders and collaboratively design Raw Vault data models using DV
Curate and manage the business glossary and metadata to support data discovery and reuse of datasets within the Enterprise Vault Layer
Work with developers to review and enable the implementation of vaults of source systems
Work with scrum masters and developers to co-ordinate, govern and plan the deployment of vaults across environments
Work with analysts and developers to ensure data completeness, consistency and accuracy through automation (data debugging)

Stakeholder Engagement
Work directly with management and other business users to gather requirements, provide status updates, and build relationships
Present information using data modelling techniques
Develop and conduct analyst training What will make you successful in this role?
**Requirements**:
**Qualifications**:
An Appropriate IT Qualification (Diploma/Degree in (statistics/data or computer science/engineering) will be a strong recommendation.
Practical experience in data modelling, data warehousing, data analysis and data profiling
Business or Systems Analyst certification will be advantageous

Knowledge and Experience
More than 5 years of experience performing data modelling or data warehouse data model build
Strong knowledge of and experience with relational databases or Hadoop Distributed File System (preferred), data modelling (Kimball or Data Vault) and querying (SQL)
Understanding of Business Intelligence and Data Warehousing software development lifecycle
Ability to perform well under pressure and manage competing priorities
Business experience in financial services an advantage
Strong analytical-thinking and problem-solving abilities
Excellent written and verbal communication skills
Experience working with data in various data sources and databases
Strong analytical skills with the ability to collect, organize, analyse, and disseminate significant amounts of information with attention to detail and accuracy
Demonstrated experience in handling large data sets and relational databases.
Experience working in an agile environment, along with working experience of SharePoint, JIRA, and Confluence
Excellent attention to detail

Competencies
Communication skills
Accountability
Analytical thinking
Innovative thinking
Building and maintaining relationships
Results driven
Team success
Adaptability Personal Attributes Manages complexity - Contributing throu