Specialist Data Engineer at Absa Group Limited (Absa)

Job Description

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

People

• Coach & mentor other engineers
• Conduct peer reviews, testing, problem solving within and across the broader team
• Build data science team capability in the use of data solutions

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)

Experience/Skills

• SQL Proficiency: Advanced knowledge of SQL for querying, managing, and manipulating databases.
• Knowledge of Big Data Technologies: Experience with big data frameworks and tools such as Apache Hadoop, Spark, Kafka, and Hive.
• Understanding of Cloud Platforms: Familiarity with cloud services like AWS, Azure, or Google Cloud Platform, specifically their data services.
• Data Modeling and Database Design: Skills in creating efficient database schemas and designing robust data models that support business requirements.
• ETL/ELT Processes: Expertise in building and managing Extract, Transform, Load (ETL) or Extract, Load, Transform (ELT) pipelines.
• Data Governance and Security: Knowledge of data governance practices, data privacy laws, and ensuring data security and compliance.
• Experience with Data Integration Tools: Proficiency in using data integration tools such as Apache NiFi, Talend, Denodo, or Informatica.
• Problem-Solving and Analytical Skills: Strong analytical abilities to diagnose issues, optimize performance, and ensure data quality and reliability.

Qualifications

Must have

• Bachelor’s Degree: In Computer Science, Information Technology, Data Science, or a related field.
• Minimum of 5 years in similar role

Optional Certifications (Not necessary)

• Certified Data Professional (CDP)
• Google Cloud Professional Data Engineer
• AWS Certified Data Analytics – Specialty:
• Microsoft Certified: Azure Data Engineer Associate
• Databricks Certified Data Engineer Associate