Data Engineer (Python, Kubernetes, Jenkins, MongoDB)

London (Greater)
30 Nov 2017
08 Dec 2017
Contract Type
Full Time

Overview of role

The data engineer will collaborate with our data scientists in our Data Insights Unit (the DIU) to create pipelines of information for the firm's investors. Whilst the DIU's data scientists test hypotheses and unravel the meaning within the data, the data engineer will build the systems that bring data in-house and develop the software that puts insights in the hands of the investors.

You will be responsible for the development and management of data acquisition and pipeline building activities, allowing us to bring together data sets from diverse sources including public sources, 3rd party vendors and internal data repositories. Familiarity with Web, (S)FTP, APIs , SQL and related ETL technologies will thus be essential to the role.

For mature and well understood data sources, you will collaborate with the data scientists to convert their models into deployable software. Balancing the competing demands of enterprise compliance (security, approvals, deployment timelines etc.) with agility (enable the data scientists to continually adjust and adapt their models) will be essential at succeeding in this role.

This will enable DIU to use advanced analytical and statistical techniques to make connections between them and to answer important questions for the Investors.

While the role's primary focus is on data acquisition, pipelining, and software development; any experience in data science will increase your understanding of your customers needs and the constraints of their models, and thus contribute to your success in this role.

Role key responsibilities

  • This is a hands on role, building data pipelines and productionising advance analytics at Schroders.
  • The person will ideally have strong technical skills in broad variety of data technologies across the stack including: Hadoop (HDFS/Hive), Python, SQL, R
  • Define and manage best practice in configuration and management of the data store. Ensure that all data and systems are managed with the highest regard for data security and upholding of our obligations to the vendors who license data to us.
  • Work with IT to align as closely as possible with the rest of the business, whilst still ensuring that the data scientists are able to innovate, research, and act with agility.

Work with Data & Insights Technology colleagues to create and optimise ETL and data enrichment processes to maximise the usefulness of data for a variety of purposes. Includes working out how best to ingest new data sources from new vendors, and where possible directly engaging with the vendor to improve their service for Schroders' goals

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