• Permanent, Full time
  • Schroders Investment Management
  • 2018-11-16
  • London, England, United Kingdom
  • Competitive
  • Full time

Data Engineer - QEP

Data Engineer - QEP

Data Engineer/ Analyst Role Specification

Reporting to the Head of Data Analytics, QEP, the successful candidate is expected to be highly technical to work, in the first instance, with our research data however it is expected that many of the techniques and building blocks used to build it will be transferrable to the production dataset.

Key Responsibilities:

• Build and maintain a scalable database for time series
• Validation and automatic/ manual correction of errorneous data
• Quantitative analysis of investment signals using traditional, sparse and unstructured data sources
• Undertake ad-hoc development, implementing bug fixes, BAU enhancements and process improvements as required
• Follow IT standards for documentation & system access

Person Profile:

• Great problem solving and technical skills
• Ability to deal credibly with business and technical users at all levels of the organisation
• Ability to operate under pressure and deliver to demanding deadlines
• A genuine team player
• Ability to adapt to rapidly changing requirements
• Strong self-organisation, time management and prioritisation skills
• Inter-personal skills; tact, patience, courtesy, good listening skills
• Excellent verbal and written communication skills and a service-orientated approach coupled with a "can-do" attitude

Essential Skills:

• Experience of building highly scalable and high performance databases
• Strong knowledge large scale database technologies (such as Data Marts/ Cubes, Time Series, Cloud)
• Strong knowledge of MS SQL Server, T-SQL
• Knowledge of at least one Data Analytics programming language (such as Matlab/ R/ Python etc)
• A proven ability to pro-actively identify erroneous data
• Good knowledge (or the desire to obtain) of financial datasets

Desirable Skills:

• A good understanding of equity capital markets/ products
• A good understanding of fundamental accounting data
• An understanding of Quantitative Equity Strategies and their implementation
• Building Cloud enabled systems
• Matlab, .Net, VBA / Excel
• Experience of using large scale data analysis stack (Spark, Hive HQL etc..)