Engineering & development


Data developer, engineer, python, linux, bash, sql

12 October England - Greater London, City of London Temp

Team Overview

The Data & Insights technology team was established in early 2015 with the aim of delivering data insights capabilities and tools to serve the analytics needs of the business. Success has led to this team extending to a broader role within Schroders, including supporting the Data Insights Unit ("DIU")

The DIU are a team of data scientists tasked with helping investors within Schroders (i.e. Analysts and Fund Managers) make better investment decisions by better use of data. The DIU typically works with historical data (e.g. share price etc) as well as new alternative data sets -essentially acting as an R&D department for Investment.

Overview of role

The data developer/ 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, ftp, api, 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.