Current Openings at Boardroom Appointments

Minimum Requirements:

• Grade 12
• At least 3-5 years in a HMR (Home Meal Replacement) and/or Quick Sales Restaurant (QSR) Sales environment
• Sales or Marketing Diploma or equivalent

Key Competencies Skills & Knowledge:

• Manage and enhance good customer relations
• Financial and business acumen
• Trade execution of business plans
• Analyse sales and financial information
• Planning and organizing
• Ability to drive sales volume achievement
• Negotiation skills
• Understands & apply Customer Intimacy i.e. the selling the Total Solution
• Product knowledge
• Practical application of our product range
• Analytical Ability
• Computer skills

Responsibilities:

• Sales Target Achievement
• Achievement of Monthly and Quarterly Sales/ Gross Profit Targets as set by Management
• Customer Business Planning
• Plan how to achieve sales targets for each of the customers within the sales product range.
• Analyse sales performance by product and formulate plans to counteract opposition activities.
• Plan territory calls as per call cycle.
• Identify new business opportunities and alternative sales opportunities within territory and formulate sales objectives.
• Sales Activities
• Negotiate orders within given and approved parameters.
• Execute promotional activities
• Initiate ad-hoc activities.
• Complete pricing surveys.
• Identify sales opportunities
• Increase basket of products sold to customers.
• Sales Admin and Financial Control
• Update customer records.
• Maintain control over debtors payments where necessary.
• Attend stock takes.
• Provide documentation for new accounts including credit application form new and updates.
• Attend sales meetings / conferences / training courses.

go to method of application »

Key Responsibilities:

• Generate and issue client invoices accurately and in a timely manner.
• Verify billing details, rates, and terms of service.
• Resolve billing discrepancies and address client inquiries related to invoices.
• Maintain an organized record of all invoices and related documentation.
• Calculate and process employee wages and commissions in accordance with employment contracts and legal requirements.
• Maintain payroll records, including time sheets and expense claims.
• Address payroll inquiries from employees and ensure timely payment.
• Enter financial data accurately into accounting and payroll software.
• Perform regular reconciliations to identify discrepancies and rectify them promptly.

Qualifications:

• Matric and Relevant Tertiary Qualification
• Proven experience in invoicing, payroll, or finance-related roles.
• SAGE experience essential 
• Strong attention to detail and accuracy.
• Excellent organizational and time-management skills.
• Strong communication and interpersonal skills.
• Ability to maintain confidentiality and handle sensitive information.

go to method of application »

Responsibilities

• Sourcing
• Advertising Jobs with a practical marketing introduction
• Screening
• Shortlisting
• Candidate assessment and testing
• Interviewing
• Reporting on KPIs and SLA
• Offer Management
• Employer Branding
• Mapping, creating and managing Talent pools

Requirements:

• Matric 
• Diploma / Degree in HRM or related
• Minimum of 3 years Agency Recruitment experience
• Recruitment experience must include recruiting for Banking / Finance positions
• Computer Literate (ATS, Job Portals and the full MS Office)
• Excellent communications and reporting skills
• High Energy

go to method of application »

Minimum Requirements:

• Matric, with a degree in Computer Science, Business Informatics, Mathematics, Applied Statistics/Applied Mathematics Physics, or Data Engineering.
• Certification in data, data science or artificial intelligence Experience/ Requirements
• 3 to 5 + years of data engineering experience
• 3 to 5 + years of Machine learning/ Artificial Intelligence and Statistical algorithm development.
• 3+ years of experience with any data warehouse technical architectures, ETL/ELT, and reporting/analytics tools including, but not limited to, any of the following combinations (1) SSIS and SSRS, (2) SAS ETL Framework, (3) SAP ETL Framework, (4) MongoDB ETL deployments, (5) Apache Spark and Apache Hive deployments will be beneficial.
• Working with large volumes of structured and unstructured data and leveraging them to build artificial intelligence (AI)/machine learning (ML) and predictive modelling (PM) solutions through end-to-end automated data pipelines.
• Deep and Extensive AWS knowledge and skills: Glue, S3, Lambda, IAM, Cloudformation
• The candidate having DBA ability and knowledge across at least 2 platforms (example: TSQL, SAS, PSQL, IBM VSAM and DB2 etc.) will also be beneficial.
• Some experience with the Python programming language.
• Experience with designing and implementing Cloud (AWS) solutions including use of APIs available.
• Some experience with Dev/OPS architecture, implementation and operation would be advantageous.
• Minimum bachelors degree in quantitative management (decision sciences) or Computer Science/Statistics/Applied Statistics/Applied Mathematics
• Knowledge of Engineering and Operational Excellence using standard methodologies. 
• Best practices in software engineering, data management, data storage, data computing and distributed systems to solve business problems with data.
• Some experience in applying SAFe/Scrum/Kanban methodologies would be advantageous.
• Knowledge and understanding of business process management lifecycle which covers the design, modeling, execution, monitoring, and optimization as well as business process re-engineering.
• Good problem-solving skills: The ability to exercise judgment in solving technical, operational, and organizational challenges, to identify issues proactively, to present solutions and options leading to resolution
• Good programming, performance tuning and troubleshooting skills, using the latest popular programming languages such as Python, scala, java and suite of Microsoft languages C# and F# preferable

Responsibilities:

• Undertake the processing of structured and unstructured data to utilize in data science activities.
• Support the data analysis of large information to discover trends and patterns and provide feedback to the business.
• Assist in designing and implementing scalable and robust processes for ingesting and transforming datasets.
• Design, implement, and support the creation and maintenance of data pipelines from a multitude of sources.
• Ingest large, complex data sets that meet functional and non-functional requirements.
• Implement and train machine learning (ML), predictive analytics, data mining, and artificial intelligence (AI) models to perform predictions and forecast behavior and transactions, via the use of data, to enable the business to be proactive in decision-making.
• Working with large volumes of structured and unstructured data and leveraging them to build artificial intelligence (AI)/machine learning (ML) and predictive modelling (PM) solutions through end-to-end automated data pipelines.
• Enable the business to solve the problem of working with large volumes of data in diverse formats, and in doing so, enable innovative solutions.
• Design and build bulk and delta data lift patterns for optimal extraction, transformation, and loading of data.
• Supports the organisations cloud strategy and aligns to the data architecture and governance including the implementation of these data governance practices.
• Engineer data in the appropriate formats for downstream customers, risk, and product analytics or enterprise applications.
• Development of APIs for returning data to Enterprise Applications.
• Assist in identifying, designing, and implementing robust process improvement activities to drive efficiency and automation for greater scalability. 
• This includes looking at new solutions and ways of working and being at the forefront of emerging technologies.
• Work with various stakeholders across the organization to understand data requirements and apply technical knowledge of data management to solve key business problems.
• Provide support in the operational environment with all relevant support teams for data services.
• Create and maintain functional requirements and system specifications in support of data architecture and detailed design specifications for current and future designs.
• Support test and deployment of new services and features.