Lead Data Engineer - Johannesburg

Job Summary

• Leveraging a thorough understanding of the business data requirements & own data subject matter expertise ahead of trend, set data architecture direction & lead the agile solution design, deployment, implementation & ongoing optimization of enterprise wide data retrieval, storage and distribution across an estate.

Job Description

Data Architecture & Data Engineering

• Take 'one stop shop' accountability for the retrieval, storage, processing & distribution of data across a business area data eco-system
• Collaborate with data science teams & broader business & technical stakeholders to analyse customer data requirements & leverage analysis to identify & accurately spec / frame & set the appropriate data architecture for the business area
• Take accountability for deeply understanding the technical landscape and bank wide architecture that is connected to or dependent on the business area supported in order to effectively design & deliver data solutions architecture, pipeline etc.
• Leverage expertise in analytical & creative problem solving to synthesise data solution designs build a solution from its components beyond the analysis of the problem
• Lead design thinking processes to successfully deliver data solution blueprints & associated roadmaps
• Leverage state of the art relational and No-SQL databases as well integration and streaming platforms do deliver sustainable business specific data solutions.
• Lead the end to end solution design & implementation process for all data retrieval, storage & distribution solutions including contributing to and in some cases lead all phases of the development lifecycle including e.g. design process
• Develop high quality data retrieval, storage & distribution design and architecture in a test driven & domain driven / cross domain environment
• Build analytics tools that utilize the data pipeline by quickly producing well-organised, optimized, and documented source code & algorithms to deliver technical data solutions
• Create & Maintain Sophisticated CI / CD Pipelines authoring & supporting CI/CD pipelines in Jenkins or similar tools and deploy to multi-site environments – supporting and managing your applications all the way to production
• Automate tasks through appropriate tools and scripting technologies e.g. Ansible, Chef
• Debug existing source code and polish feature sets.
• Assemble large, complex data sets that meet business requirements & manage the data pipeline
• Build infrastructure to automate extremely high volumes of data delivery and
• Creatively solve data volume and scaling challenges.
• Create data tools for analytics and data science teams that assist them in building and optimizing data sets for the benefit of the business
• Ensure designs & solutions support the technical organisation principles of self-service, repeatability, testability, scalability & resilience
• Apply general design patterns and paradigms to deliver technical solutions
• Inform & support the infrastructure build required for optimal extraction, transformation, and loading of data from a wide variety of data sources.
• Continuously optimise, improve & automate data retrieval, storage & distribution processes
• Work across the value chain and in particular with QA & CSO to define and implement quality assurance routines & processes
• Work across the value chain and in particular with QA & CSO to ensure the undisputable separation, security & quality of the organisation's data
• Meaningfully contribute & ensure solutions align to the design & direction of the Group Architecture & in particular data standards, principles, preferences & practices. Short term deployment must align to strategic long term delivery.
• Meaningfully contribute & ensure solutions align to the design and direction of the Group Infrastructure standards and practices e.g. OLA's, IAAS, PAAS, SAAS, Containerisation etc.
• Strategically & operationally monitor the performance of data products and services ensuring ongoing optimization & cost to value for our businesses think bank wide
• Stay ahead of the curve on data retrieval, storage & distribution technologies & processes global best practices & trends to ensure best practice

People

• Coach & mentor other engineers
• Conduct peer reviews, testing, problem solving within and across the broader team
• Provide technical subject matter expertise and support in the attraction and recruitment of Product Engineers for the organization
• Participate as a subject matter expert in the development & development planning of the broader dat engineering team
• Support the people change teams in the design of adoption processes Customer, Employee & 3rd Party Adoption

Risk & Governance

• Identify technical risks and mitigate these pre, during & post deployment
• Update / Design all application documentation aligned to the organization technical standards and risk / governance frameworks
• Create business cases & solution specifications for various governance processes e.g. CTO approvals
• Participate in incident management & DR activity – applying critical thinking, problem solving & technical expertise to get to the bottom of major incidents
• Deliver on time & on budget always

End Date: August 30, 2026