Build solutions that ingest data from source systems into our big data platform, where the data is transformed, intelligently curated and made available for consumption by downstream operational and analytical processesCreate high quality code that is able to effectively process large volumes of data at scale Put efficiency and innovation at the heart of the design process to create design blueprints (patterns) that can be re-used by other teams delivering similar types of workUse modern engineering techniques such as DevOps, automation and Agile to deliver big data applications efficientlyProduce code that is in-line with team, industry and group best practice using a wide array of engineering tools such as GHE (Github Enterprise), Jenkins, Urbancode, Cucumber, Xray etcWork as part of an Agile team, taking part in relevant ceremonies and always helping to drive a culture of continuous improvement Work across the full software delivery lifecycle from requirements gathering/definition through to design, estimation, development, testing and deployment ensuring solutions are of a high quality and non-functional requirements are fully considered Consider platform resource requirements throughout the development lifecycle with a view to minimising resource consumption Once Cloud is proven within the bank, help to successfully transition on-prem applications and working practices to GCPAbout YouPrior experience doing technical development on big data systems (large scale Hadoop, Spark, Beam, Flume or similar data processing paradigms), and associated data transformation and ETL experience.Coding experience in Java or ScalaHive, Pig, Sqoop and knowledge of Data transfer technologies such as Kafka, Attunity, CDC are a bonusGCP or Cloud expertise is a plusPassionate about data and technologyExcellent people and communication skills, able to communicate with technical and non technical colleagues alikeGood team player with a strong team ethos