Head, Data Engineering
Head, Data Engineering
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Job Description
To develop and maintain complete data architecture across several application platforms provide capability across application platforms. To design build operationalise secure and monitor data pipelines and data stores to applicable architecture solution designs standards policies and governance requirements thus making data accessible for the evaluation and optimisation for downstream use case consumption. To execute data engineering duties according to standards frameworks and roadmaps.
Acquire datasets that align with business needs and requirements to enable useful and actionable information providing feedback on the clarity and completeness of data requirements. Analyse data elements and systems data flow dependencies and relationships to ensure conceptual physical and logical data models
Apply subject matter expertise into decisions relating to data engineering and data integration. Educate internal stakeholders on data engineering and data integration perspectives on new approaches
Build required infrastructure for optimal extraction transformation and loading of data from various data sources using various technologies (i.e. AWS and SQL technologies). Build create manage and optimise data pipelines move data pipelines into production enabling data consumers to utilise data for reporting purposes
Collaborate with insights teams Technology engineers and Data & Analytics leadership to identify opportunities for process improvements recommend system modifications and give input to the development of policies for data governance
Contribute to automation initiatives and guide the identification design and implementation of internal process improvements automation of manual processes optimising data delivery re-designing infrastructure for greater scalability etc
Design document and implement processes for executing partner system alignments communicating these with the relevant stakeholders including Governance. Continually enhance processes to deal with the dynamics of partner systems alignment
Develop across several application platforms provide capability across application platforms construct test and maintain complete data architecture allowing for data-led and data driven decision making
Enable and execute internal and external data migrations across different databases applications servers and define and implement data stores based on system requirements and business consumer requirements
Execute on the design definition and development of Application Programming Interfaces (APIs) aligning to relevant frameworks and guidelines. Create data tooling enabling data consumers in building and optimising data consumption taking integration and usage patterns into account
Guide and manage a small team to develop across several application platforms and provide capability across application platforms
Identify design and implement internal process improvements including re-designing infrastructure for greater scalability optimising data delivery and automate manual processes
Liaise and collaborate with technology colleagues and segment/country data teams to understand viable data solutions within architectural guidelines
Make data accessible by interpreting business requirements defining and providing technology solutions that collect manage and convert raw data into usable information to be interpreted by data consumers and insights teams. Take part in to ensure the deployment of solutions in accordance with applicable architecture solution designs standards policies and governance requirements
Participate in the vetting and promoting of content created in the business for business reuse
Partner with Information security teams to safeguard and ensure compliance with data governance and data security requirements while creating improving and operationalising integrated and reusable data pipelines
Pro-actively perform analyses of data to identify and recommend optimisation and improvements and enable proactive analysis and evaluation of the databases to identify and recommend improvements and optimisation
Research data integration warehousing and reporting best practices ensuring applicable standards are adhered to and applied in the solution design
Shape data traceability standards guidelines and processes to ensure data quality by guiding processes such as keeping track of data sources and setting up appropriate data version control processes and systems ensuring alignment to defined data architecture
Qualifications :
Type of Qualification: First Degree
Field of Study: Business Commerce
Type of Qualification: First Degree
Field of Study: Information Studies
Type of Qualification: First Degree
Field of Study: Information Technology
Experience Required
Software Engineering
Technology
5-7 years
Experience in building databases warehouses reporting and data integration solutions. Experience building and optimising big data data-pipelines architectures and data sets. Experience in creating and integrating APIs. Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement
8-10 years
Deep understanding of data pipelining and performance optimisation data principles how data fits in an organisation including customers products and transactional information. Knowledge of integration patterns styles protocols and systems theory
8-10 years
Experience in database programming languages including SQL PL/SQL SPARK and or appropriate data tooling. Experience with data pipeline and workflow management tools
Additional Information :
Behavioural Competencies:
- Adopting Practical Approaches
- Articulating Information
- Checking Things
- Developing Expertise
- Documenting Facts
- Embracing Change
- Examining Information
- Interpreting Data
- Managing Tasks
- Producing Output
- Taking Action
- Team Working
Technical Competencies:
- Big Data Frameworks and Tools
- Data Engineering
- Data Integrity
- Data Quality
- IT Knowledge
- Stakeholder Management (IT)
Remote Work :
No
Employment Type :
Full-time
Employment Type
Full-time
