Cloud Data Engineering – Are you able to work behind the scenes to obtain, process and supply data via various methodologies and technologies, to various consumers, in ways and forms that makes sense and adds value?
Do you have a broad understanding of Data Management (DMBOK)?
Personal competencies that we are looking for:

The ability to solve problems.
The ability to rotate around a problem, to see if solutions can be gained in different ways.
The ability to work in an ever changing, unstructured environment.
The ability to work as part of a team, with vastly differing skill sets and opinions.
The ability to contribute ideas to the quorum.
The ability to mentor and provide guidance for other team members.
A systems approach to thinking, as opposed to a siloed approach. You need to understand how your work affects the greater system.
The ability to work without supervision and take accountability for the work you deliver.
The ability to liaise with clients, the ability to ignore extraneous data and extracting the core requirements.

RESPONSIBILITIES:
As a Data Governance Analyst:

Developing and implementing data standards, guaranteeing metadata is captured correctly, and creating methods for monitoring and reporting any data incidents.
Monitoring of application personnel to ensure adherence to data governance and regulatory requirements, where required.
Create and maintain common data dictionaries/business glossaries and the tools or methods that support data standards for an organization.
Analyse and oversee strategies designed to enhance data reliability and minimize redundancies.
Work with other information technology personnel to develop data quality standards.
Create key performance indicators and supply colleagues and organizational management with performance results.
Assist with data monitoring and provide organizational management with guidance on streamlining data management.
Implement procedures and policies for data management in an organization, assisting colleagues in performing data-related tasks, and networking with clients.

As a Data Analyst:

Interpret data, analyse results and interpret trends enabling continuous improvement in data quality and overall business performance
Create detailed specifications that specify data sources, data flows, data transformations, data storage and reporting
Produce documentation such as source-to-target-maps, data dictionaries and data models
Create test cases and scenarios used to ensure quality assurance
Interact and collaborate with technical and business stakeholders to identify data sources, find data definitions for master and metadata as well as formulate and implement solutions
Promote the use of existing enterprise and divisional data standards to enhance data quality, ensure constant compliance and adherence to data governance principles
Promote reusability, maintainability, reliability, and scalability in design and development of data solutions
Process live and confidential data according to specified guidelines
Evaluate changes and updates to source production systems that could impact reporting and eventually business decisions

As a Data Modeller:

Modelling data changes required by new features or regulatory needs
Contribution in filling any gaps in the wider enterprise models
Ensuring that the data model is aligned to the wider enterprise models, raising issues for any exceptions
Collaborating with the business analysts, product teams and architects to build data flow and develop conceptual models
Perform reverse engineering of physical data models
Coordinate data models, dictionaries, and other database documentation across multiple applications
Identify opportunities to improve business
Provide Data Management guidance and alignment to the Data Management framework and standards
Collate dataflow diagrams outlining the flow of data across systems and interfaces
Support the achievement of the business strategy, objectives, and values

As a Cloud Data Engineer:
(As the field of data engineering is very broad, you may be required to develop API endpoints for the consumption of data, data pipelines, highly distributed, high availability data processing pipelines in an effort to satisfy the need of the Client, Data Analysts or Quantitative Analysts.)

Providing a superior customer experience by building and maintaining relationships, working at customer offices, keeping data confidential
Design and develop data solutions
Produce solutions for both real-time and batch environments
Test your work to ensure compliance
Solve problems, and do root cause analysis
Prioritize your workload
Assist in other areas relating to your data function, such as data modelling, data and business analysis
Interact with a variety of individuals: senior, junior and technical business representatives
Provide guidance to colleagues or manage a team
Uphold the IQbusiness values, which are to care, learn ’ share; innovate; deliver as well as to build, enhance and maintain relationships.

REQUIREMENTS:
For a Data Governance Analyst:

7-10 years of experience in Data Management Framework development and implementation thereof
Relevant Bachelors’ Degree / Diploma / recognised qualification from an accredited tertiary institution preferably ICT
Knowledge and/or experience in Data frameworks, practices and tooling (e.g., DAMA, Apache, etc)
Demonstrates knowledge of database and data warehouse design
Proven experience building logical and physical data models using industry best practices, patterns and frameworks
Has analytical skills and demonstrates a deep interest in research
Demonstrates the ability to collect, organize, analyse, and disseminate significant amounts of information with attention to detail and accuracy
Ability to draw actionable insights from raw data and information to help further the business’s cause
Ability to communicate well with different types of stakeholders, adapt to different project environments and play a flexible role in projects
Have a drivers' license and a willingness to travel

For a Data Analyst:

3 – 6 years of experience in analyzing and using data to solve problems
Relevant Bachelors’ Degree / Diploma / recognised qualification from an accredited tertiary institution preferably ICT
Knowledge and/or experience in Data frameworks, practices and tooling (e.g. DAMA, Apache, etc)
Demonstrates knowledge of database and data warehouse design
Proven experience building logical and physical data models using industry best practices, patterns and frameworks
Practical technical experience using database management tools(SQL) and reporting tools(Power BI)
Familiarity with BI methodologies such as Kimball and Inman
Has analytical skills and demonstrates a deep interest in research
Demonstrates the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy
Ability to draw actionable insights from raw data and information to help further the business’s cause
Ability to communicate well with different types of stakeholders, adapt to different project environments and play a flexible role in projects
Have a drivers' license and a willingness to travel

For a Data Modeller:

Able to demonstrate practical experience in relational and dimensional modelling techniques, modelling experience also an advantage
Experience using Infosphere Data Architect or any other Data Modelling Tool
Experience with industry models such as IFW, BFMDW
Broad understanding of Data Management (DMBOK), systems development lifecycle methodologies and IT Architecture
Relevant regulatory knowledge, and understanding of banking and financial services
Experience in NoSQL and other forms of database modelling advantageous
SQL for Data Analysis
Denodo experience would be advantageous
Matric and NQF level 6 Qualifications essential
BCom or BSc Computer science or Information systems advantageous
DAMA, TOGAF and the like highly beneficial.

For a Cloud Data Engineer:

4 – 10 years experience in Data Engineering environments and technologies
Cloud exposure and/or project experience – Microsoft Azure, AWS, etc
Extensive experience in Microsoft Azure technologies
Extensive experience in reporting and dashboarding technologies such as Power BI and QlikView
Experience using Azure DevOps and CI/CD frameworks
Exposure to logical and physical data modelling
Agile and waterfall project management
Relevant Qualifications Information Technology
Additional MS, Data and/or Cloud certifications are beneficial.

Your knowledge about the following concepts, is valuable to the team:

Data modelling
Relational data modelling in traditional database management systems
Coercing unstructured and semi-structured data into structured form
Data pipeline knowledge (extracting and transformation)
Data transformation knowledge for reporting and analytics purposes

Some technical competencies that we are looking for:

Writing SQL queries, that can relate, transform and aggregate data from many different sources
Experience with writing data pipelines that move and transform data
Working knowledge of a general purpose programming language like Python would be advantageous
Working knowledge of Microsoft Azure technologies such as Azure Data Factory, Azure SQL, Databricks, Synapse Analytics.
Working knowledge of Storage Repositories and Data Lakes