The Bank of England is the UK's central bank. Our mission is to deliver monetary and financial stability for the British people.

The Bank of England is a diverse organisation. Each of its 4,000 plus people are committed to public service and dedicated to promoting the good of the people of the United Kingdom by maintaining monetary and financial stability.

Our team, the Data Management Hub (DMH) is relatively new and growing rapidly. Our Division has developed the Bank's Data Strategy, and our task is to own and be responsible for key elements of its implementation.

Why Join The Bank of England?

• Meaningful, high-profile work. The Bank’s data and analytical (D&A) outputs ultimately result in decisions of national importance. The Governor has made D&A enablement a key strategic priority!
• We are a historic institution with a rich history (over 325 years old), and important standing in UK public life.
• We value Diversity and Inclusion and the benefits of different ideas being built by people from different backgrounds.
• We support personal development and growth. We encourage learning, and ‘empowering others’ is a core value we are supervised on.
• Our overall financial package is competitive: Typically, it involves base salary + an additional 7% extra (to spend on benefits or take as cash) + private medical + employee income protection + performance bonus + generous pension contribution (whereby no salary sacrifice is required from you!).

The Opportunity

This role will focus on the Data Quality (DQ) service within DMH. Ensuring our data is ‘fit-for-purpose’ is a core component of our Data Management function. This is an opportunity to use your data analysis skills (e.g. R or Python, combined with SQL and Excel) to define and self-develop best-practice DQ controls via the direct querying of data. In addition, surfacing DQ measurements through visualisations (e.g. in Tableau) to monitor data, report on it, and inform others before they use it, is also critical to realising our DQ value-proposition.

We don’t stop there! Once you identify DQ issues, you will undertake root-cause-analysis, opine on fixes or workarounds, and in some cases cleanse the data yourself. Documenting and translating business rules into technical queries will be standard practice.

Communication and presentation skills are also integral to the role, and where required you will need to call out DQ issues to the relevant Data Owners, Boards or Committees.

Team members are proactive and self-sufficient, as you will be entrusted with the freedom to work independently with mentorship from a line manager. In return, there will be an expectation to demonstrate activity that results in good business outcomes and overall progress towards objectives.

Links-ups and occasional collaboration with other D&A services across the Bank such as Master Data Management, Data Registration (data cataloguing), Metadata Management, Data Architecture, Data Collections and other Analytics teams, will be routine so co-operation and flexibility is a must.

Role Requirements

Essential Criteria

• You must be proficient in interrogating data, preferably via R.
• Working knowledge of Python, SQL and MS Excel will also help you succeed in the role.
• Proficient in the creation of dashboards and other visualisations using Tableau.
• Able to build analytical queries to examine the dimensions of DQ: accuracy, completeness, consistency, timeliness, validity, and uniqueness.
• Experience of interpreting business rules to define and implement DQ controls.
• Able to promote DQ so the business understands why it is important and benefits it brings.
• Able to provide internal consultation to projects and other teams on ideal preventative DQ controls as well as detective DQ controls they can build.

Desirable Criteria

• Experience of querying Big Data environments, specifically HDFS (Hadoop) or cloud based lakes or marts.
• Experience of presenting technical solutions and findings to both technical and non-technical partners, tailoring your content accordingly.
• Understand and be able to articulate the link between DQ and other functions in the business e.g. Operations, Risk and Compliance, Data Privacy.
• Able to unpack a variety of file types e.g. txt, csv, XML, json for analysis.