CLOUD ENGINEER BRAMBLES DIGITAL (DATA MANAGEMENT)

Position: Cloud Engineer Brambles Digital (Data Management)– UK or MadridPosition PurposeCloud Engineers set up, operate, develop, evolve, and maintain cloud-centric platform(s) including IoT, Customer Solution Delivery, Data Science Environments and Software Delivery, as well as satellite tools and environments (file storage, databases, tensorflow, data streaming, eventing, machine learning and big data frameworks, notebook technologies, and container orchestration tooling).Location: UK or Madrid.Measures:Successful roll out, development and continuous evolution and operation of cloud-based data science and machine learning platforms, IoT, Edge and Software Delivery frameworks, both for research & development and for continuous operationEffective support of data science projects, digitisation projects and software delivery projectsReliability of systems Adoption of systemsMajor/Key Accountabilities Design, develop, release and operate databases including high availability, replication, backup and recovery, resilience, stability, tuning, performance and scalability which are used by application software development teams and software operations teams. Also engage with these teams, to improve and extend the existing database tooling and usage. The purpose is to enable them to scale, and focus on feature development, by providing a common technical platform / infrastructure, and improving developer experience.Develop, release, operate these underlying cloud databases including but not limited to TimescaleDB, Postgres, DuckDB, Redis, etcd, SpiceDB, Redshift, Graph Databases, Columnar databases and more. A special focus on TimeScaleDB self-managed instances at scale for IOT data of different types for different applications.Design new tools and improve/extend existing data management tooling by engaging with key stakeholders and team leadsSupport and train tool users in application development and software operations teamsResponsible for learning, operating, evolving, contributing to, and maintaining Brambles Digital bespoke frameworks that support the BRIX platformResponsible for rigorous testing of framework and datastore, database robustness and scalabilityWill contribute to data science / engineering teams discussions, providing insight as needed on other team member’s current approaches and methods as well as on tools and data repositoriesLiaise with Brambles Digital Cloud Engineering / BRIX digital operations, in order to understand current software operation and operation tooling Build and maintain Continuous Integration and Continuous Deployment pipelines used in the release process Operate and monitor software services running in a Kubernetes environment, and natively on AWS.Responsible for contributing to capability building of the team, including researching and staying up-to-date on best practices e.g. Platform Engineering, GitOps, IaC (infrastructure as code), DataStores, Databases, Data Storage technologiesCreate user documentation, troubleshooting guides, FAQs for software tools, and services. QualificationsEssentialBS degree in Data Science, Computer Science, Engineering, Math, Statistics, Physics, or similar formal training or equivalentDesirable QualificationsProven experience with looking after data recovery and database high availability and database tuningProven experience with FinOps and being able to optimise spend for CE impactExperience with working with IoT and Edge interaction with the CloudExperience5yr relevant experience in Cloud Engineering or adjacent fieldsInstalled, operated, and managed several data science and machine learning frameworks, or developed own data science methodologiesExperience with Continuous Integration and Continuous DeploymentExperience operating, optimising, querying, and administering databases (such as Postgres, TimescaleDB, etc.)Comfortable using and working in a polyglot computer language environment (Python, Go, Julia etc.)Experience with Amazon Web Services (S3, EKS, ECR, EMR, etc.)Experience with containers and orchestration (e.g. Docker, Kubernetes)Experience with Big Data processing technologies (Spark, Hadoop, Flink etc) Experience with interactive notebooks (e.g. JupyterHub, Databricks)Experience with Git Ops style automationExperience with *ix (e.g, Linux, BSD, etc.) tooling and scriptingParticipated in projects that are based on data science methodologies, and/or physical experiments, or statistical analysis – especially in a data engineer and dev ops capacity.Skills and KnowledgeKnowledge of major data science and dev ops frameworks and methodsVery strong analytical skills and systems thinkingStrong programming skills in addition to operational skills a plus (ideally in one or more of the following languages: Python, Go, Julia, or C/C++)Attention to big picture and details