|Location||Sandton, Gauteng, South Africa|
Blue Label Telecoms are a JSE-listed company that sells innovative technology for mobile commerce to emerging markets in South Africa and abroad. Our users are rich, poor, urban and rural, and we allow them all to interact and transact on an equal footing. We reach them by using both physical and virtual distribution channels. We target many of our services at people who do not have easy access to bank accounts, and we allow them the convenience of being able to transact where and when they want to. Our good reputation is our license to operate.
|Job Functions||Information Technology|
Responsible for building the organisations data collection systems and processing pipelines. Oversee infrastructure, tools and frameworks used to support the delivery of end-to-end solutions to business problems through high performing data infrastructure. Responsible for expanding and optimising the organisations data and data pipeline architecture, whilst optimising data flow and collection to ultimately support data initiatives.
Owns and extends the business’s data pipeline through the collection, storage, processing, and transformation of large data-sets and oversees the process for creating and maintaining optimal data pipeline architecture and creating databases optimized for performance, implementing schema changes, and maintaining data architecture standards across the required Standard Bank databases.
Oversee the assembly of large, complex data sets that meet functional / nonfunctional
business requirements and align data architecture with business requirements.
Responsible overseeing the process for enabling and running data migrations across different databases and different servers and defines and implements data stores based on system requirements and consumer requirements.
Oversee, design, and develop algorithms for real-time data processing within the business and to create the frameworks that enable quick and easy access to relevant data.
Build analytics tools that utilise the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
Create data tools for analytics and data scientist team members that assist them in building and optimising xxxxxxxxx into an innovative industry leader.
Monitor the existing metrics, analyse data, and lead partnership with other Data and Analytics teams in an effort to identify and implement system and process improvements.
Utilise data to discover tasks that can be automated and identify,
design, and implement internal process improvements: automating manual
processes, optimizing data delivery, re-designing infrastructure for greater
Developing ETL processes that convert data into formats for consumption.
Risk, Regulatory, Prudential and Compliance
Responsible for executing testing and validation in line with data governance and quality business requirements.
Liaise with and collaborate with data analysts, data warehousing engineers, and data scientists in finding and applying best practices within the Data and Analytics department as well as defining the business’s data requirements, which will ensure that the collected data is of a high quality and optimal for use across the department and the business at large.
Acts as a subject matter expert from a data perspective and provides input into all decisions relating to data engineering and the use thereof.
Provide guidance in terms of setting governance standards.
Responsibility for contributing to the continual improvement of the business’s data platforms through thorough observations and well-researched knowledge.
Keeps track of industry best practices and trends and through acquired knowledge, takes advantage of process and system improvement opportunities.
Provide oversights and expertise to the Data Insights and Analytics that is responsible for the design, deployment, and maintenance of the business’s data requirements.
Business Requirements Identification
Elicit the most complex business requirements using a variety of methods such as interviews, document analysis, workshops, and workflow analysis to express the requirements in terms of target user roles and goals.
Insights and Reporting
Contribute to the design and creation of reporting strategies and templates.
Lead execution of complex reports, identifying and interpreting complex patterns and trends, and translating those insights into actionable recommendations.
Budgeting and Costing
Develop and/or deliver budget plans with guidance from senior colleagues.
Digital Culture Creation
Integrate digital capabilities into processes, projects, and team dynamics.
Execute and champion transformational projects intended to develop a digital culture.
Digital Vision and Strategy
Conceptualize elements of digital strategy/digital-enabled business change projects. Develop approaches to programmatically deliver successful digital innovation engagements.
Digital Strategy/Transformational Projects Execution
Manage and deliver end-to-end digital programs and initiatives, leveraging agile and design-thinking principles to drive sustainable implementation.
Performance Improvement through Business Intelligence
Create complex algorithms that identify patterns in structured data through supervised and unsupervised data.
Manage data preparation in collaboration with different stakeholders/internal clients in the business.
Manage and report on the performance of a substantial, diverse team; set appropriate performance objectives for direct reports or project / account team members and hold them accountable for achieving these; take appropriate
corrective action where necessary to ensure the achievement of team / personal
Optimizes Work Processes.
Plans and Aligns.
Policy and procedures.
Customer and Market Analysis.
IT Data Management.
Post Graduate Degree: Information Technology.
Post Graduate Degree: Information Studies.
Masters Degree: Information Technology.
Masters Degree: Information Studies.
Apache Spark. (supports programming languages Python, Scala, Java, and R) C++.
Amazon Web Services.
Important Hard Skills:
Database systems (SQL and NoSQL).
Data engineer must know how to manipulate database management systems (DBMS), which is a software
application that provides an interface to databases for information storage and retrieval.
Data warehousing solutions.
ETL (Extract, Transfer, Load).
Allows two applications or machines to communicate with each other for a specified task.
Python, Java, R and Scala programming languages.
Understanding the basics of distributed systems.
Important Soft Skills:
Interface with machine learning engineers, data analysts,
CTOs, and developers.
They may also work with other teams or business units to gather requirements and define the scope of a project.
Need to understand the expectations of the teams they’re working with, how frequently they need to be updated, and what their pain points are.
May be expected to perform data analysis and present their findings to stakeholders.
|Job Closing Date||22/04/2021|