The Data and Enterprise Services is a dynamic team within the Digital and Data division. We seek to create seamless and personalized experiences for our 13 million customers globally. Its core purpose is to design, implement and support key datasets that provide structured and timely access to actionable business information whilst championing the needs of the customer always. The Digital & Data team applies customer-focused design thinking, data management, cloud engineering, agile and lean development methodologies, and continuous delivery practices in its deliveries.
This teams primary focus is to build and establish the data platform capability by applying industry knowledge, best practices and innovative ideas to take the Company into the future through the use of best of the breed technologies and applied thinking and processes on its strategic journey to the cloud.
To complement the existing cross-functional team, we are looking for a Senior Data Engineer who will design and implement scalable and robust processes to support the data engineering capability. This role will be responsible for implementing and supporting large-scale data ecosystems across the Group. This thought leader will use best practices in cloud engineering, data management and data storage to continue our drive to optimize the way that data is stored, consumed and ultimately democratized. The incumbent will also collaborate with stakeholders across the organisation with use of the Data Engineering practices to facilitate the improvement in the way that data is stored and consumed.
KEY AREAS OF RESPONSIBILITIES:
- Design and implement 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.
- 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 bulk and delta data lift patterns for optimal extraction, transformation, and loading of data.
- Ensure that all data solutions support the organisations cloud strategy and aligns to the data achitecture and governance including implementation of these data governance practices.
- Engineer data in the appropriate formats for downstream customers, risk and product analytics or enterprise applications.
- Engineer the development of APIs for returning data to Enterprise Applications.
- Identify, design and implement robust process improvement activities to drive efficiency and automation for greater scalability. This includes looking at new solutions and new ways of working and being on the forefront of emerging technologies.
- Work with various stakeholders across the organisation to understand data requirements and apply deep technical knowledge of data management to solve key business problems.
- Provide specialised support in the operational environment with all relevant support teams for data services.
- Effective mangement of demand across the various data streams and use cases.
- Create and maintain functional requirements and system specifications in support of data architecture and detailed design specifications for current and future designs.
ROLE & QUALIFICATIONS REQUIREMENTS
- Matric, with a degree in Computer Science, Business Informatics, Mathematics, Statistics, Physics or Engineering.
- 5+ years of data engineering experience
- 5+ years of experience with 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. The candidate should demonstrate great DBA ability and knowledge across at least 2 platforms (example: TSQL, SAS, PSQL, IBM VSAM and DB2 etc)
- Experience with designing and implementing Cloud (AWS) solutions including full use of all APIs available
- Experience with Dev/OPS architecture, implementation and operation
- 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.
- Experience in applying SAFe/Scrum/Kanban methodologies
- Knowledge and understanding of business process management lifecycle which covers the design, modelling, execution, monitoring, and optimization as well as business process re-engineering.
- Strong 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
- Expert 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.
- Collaboration and communication: working with clients, designers, architects, development team(s)
- Leading with Influence
- Customer First
- Personal Mastery (Learning)
- Problem Solving
- Data Analysis
- Working with ambiguity
- Working independently and within a team