Specialist Data Engineer at Absa Group Limited (Absa)

Job Summary

• Work embedded as a member of squad OR; across multiple squads to produce, test, document and review algorithms & data specific source code that supports the deployment & optimisation of data retrieval, processing, storage and distribution for a business area.

Job Description

Key skills and experience required:

• 5+ years relevant data and software engineering experience
• Relevant B-Degree in Computer Science preferred but not essential if minimum requirements of experience and practical application is evident

Core Data Engineering

• Proficiency in data pipeline development (batch, real-time, file-based)
• Strong experience with AWS services, especially: S3, Glue, Lambda, Step Functions, DataZone
• Familiarity with data lakehouse concepts, Hadoop/Hive, or equivalent
• Experience ingesting from diverse sources: Databases (RDBMS/NoSQL), APIs, file drops, message queues

Data Distribution and Access

• Designing reusable access layers (e.g. APIs, event streams, S3-based delivery)
• Implementing secure data access controls and RBAC
• Building scalable distribution mechanisms for on-prem and cloud consumers

Metadata, Cataloging and Governance

• Experience with data catalogs (AWS Glue, Ataccama, DataZone, or similar)
• Understanding of data lineage, classification, and metadata management
• Contributing to or building tooling for data governance and compliance

Software Engineering Best Practices

• Clean, modular design with maintainability and automation in mind
• Proficiency in Python, C#, or other relevant languages
• Experience with CI/CD pipelines, infrastructure as code, version control

Monitoring and Quality

• Designing and implementing data quality rules, SLAs, validation, and alerts
• Familiarity with centralized logging, observability, and monitoring platforms

Team and Strategy Contribution

• Ability to mentor developers and lead peer reviews
• Comfortable presenting to technical and non-technical stakeholders
• Track record of influencing data standards, architectural decisions, or best practices

Preferred Experience

• Experience with centralized ingestion frameworks or orchestrators
• Understanding of hybrid data architecture: bridging on-prem and cloud ecosystems
• Exposure to reporting platforms or BI tool integration with backend datasets

Key Accountabilities:

Data Architecture & Data Engineering

• Understand 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.)
• Translate / interpret the data architecture direction and associated business requirements & leverage expertise in analytical & creative problem solving to synthesise data solution designs (build a solution from its components) beyond the analysis of the problem
• Participate in design thinking processes to successfully deliver data solution blueprints
• Leverage state of the art relational and No-SQL databases as well integration and streaming platforms do deliver sustainable business specific data solutions.
• Design data retrieval, storage & distribution solutions (and OR components thereof) including contributing to all phases of the development lifecycle e.g. design process
• Develop high quality data processing, retrieval, storage & distribution design 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
• 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
• Support the continuous optimisation, improvement & automation of data processing, retrieval, storage & distribution processes
• Ensure the quality assurance and testing of all data solutions aligned to the QA Engineering & broader architectural guidelines and standards of the organisation
• Implement & align to the Group Security standards and practices to ensure the undisputable separation, security & quality of the organisation’s data
• Meaningfully contribute to & 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 to & ensure solutions align to the design and direction of the Group Infrastructure standards and practices e.g. OLA’s, IAAS, PAAS, SAAS, Containerisation etc.
• Monitor the performance of data solutions designs & ensure ongoing optimization of data solutions
• Stay ahead of the curve on data processing, retrieval, storage & distribution technologies & processes (global best practices & trends) to ensure best practice

Education

• Bachelor's Degree: Information Technology