Data Professional at IQbusiness

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