Specialist Data Engineer (KE)

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
  

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