You will be joining a well-established, cutting edge DevOps team within a multi-national Fintech. This senior position would work primarily with the company’s fast growing Data Science team to scale up the existing ETL pipelines, automate end-to-end data science prototyping and communications and catalogue the model-store of machine learning and deep learning models. You would also be responsible for managing the day-to-day performance of an internal data warehouse.                              

As a DevOps Engineer with a such focus, a typical day might include any of the following:

  • Managing schedulers (Jenkins) to extract data from production databases
  • Batch, shell scripting to move data within the data warehouse
  • Overseeing log-files to ensure data reporting jobs (currently c.40 per month) are running smoothly
  • Designing new work intake pipeline with business and Data Science teams to deliver new data reports
  • Jointly, with Data Scientists, designing automated communication strategies for internal and external stakeholders

You’re good at:

  • Understanding Data Scientists’ requirements for organisation and accessing data
  • Batch and/or shell (Redhat) scripting
  • Provisioning and configuration tools (Terraform, Puppet)
  • SQL Server database tasks such as backup, restore, encryption
  • Running ETL processes, based on SSIS and SSRS currently
  • Following best practices in data movement such as logs and error handling
  • Maintaining a consistent quality of work and rigorous attention to detail
  • Ability to working collaborative across teams such as Developers, IT and Data Science

Extra awesome:                              

  • Python skills
  • Additional database experience (Postgres, ElasticSearch)
  • Exposure, or willingness to learn, machine learning techniques
  • Prior experience of managing repository of machine learning models
  • Containerisation and orchestration (Docker, Kubernetes)
  • Basic networking skills                                                                                                                      

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