Cloud Automation Engineer

projects or modules to understand requirements, develop and implement
infrastructure solutions Data Engineering and Artificial Intelligence service
Infrastructure as Code (IaC), Python, Docker, Kubernetes
* Cloud Engineering (Azure, GCP, preferably AWS)
a good understanding of ML and AI methodologies
such as risk and controls, change and transformation, business acumen
strategic thinking and digital and technology, as well as job-specific
data, such as data pipelines, data warehouses and data lakes to ensure that
all data is accurate, accessible, and secure.
**Build and maintenance of data architectures pipelines that enable the transfer and processing of durable, complete and consistent data.
* Design and implementation of data warehoused and data lakes that manage the appropriate data volumes and velocity and adhere to the required security measures.
* Development of processing and analysis algorithms fit for the intended data complexity and volumes.
* Collaboration with data scientist to build and deploy machine learning models.
**Escalate breaches of policies procedure appropriately.
* Take responsibility for embedding new policies procedures adopted due to risk mitigation.
* Take ownership for managing risk and strengthening controls in relation to the work you own or contribute to. Make evaluative judgements based on the analysis of factual information, paying attention to detail.
* Act as contact point for stakeholders outside of the immediate function, while building a network of contacts outside team and external to the organisation.
All colleagues will be expected to demonstrate the Barclays Values of Respect,
Integrity, Service, Excellence and Stewardship - our moral compass, helping us
Barclays Mindset - to Empower, Challenge and Drive - the operating manual for

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