Specialist Data Engineer at Absa Bank

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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

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[1]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[1]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

Skills & Experience Required

• 3+ years relevant experience

• Proficiency in Hadoop required

• Spark and/or AWS knowledge a distinct advantage

• Experienced in lake formation

• Ability to adapt to inhouse built ETL tools

Education

Bachelor's Degree: Information Technology