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Barclays

Liquid Financing Data Engineer

London
Posted 1 day ago
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Job Description

Purpose of the Role

To use innovative data analytics and machine learning techniques to extract valuable insights from the bank's data reserves, leveraging these insights to inform strategic decision-making, improve operational efficiency, and drive innovation across the organisation.

Accountabilities

  • Identification, collection, extraction of data from various sources, including internal and external sources.
  • Performing data cleaning, wrangling, and transformation to ensure its quality and suitability for analysis.
  • Development and maintenance of efficient data pipelines for automated data acquisition and processing.
  • Design and conduct of statistical and machine learning models to analyse patterns, trends, and relationships in the data.
  • Development and implementation of predictive models to forecast future outcomes and identify potential risks and opportunities.
  • Collaborate with business stakeholders to seek out opportunities to add value from data through Data Science.

Vice President Expectations

  • To contribute or set strategy, drive requirements and make recommendations for change. Plan resources, budgets, and policies; manage and maintain policies/ processes; deliver continuous improvements and escalate breaches of policies/procedures.
  • If managing a team, they define jobs and responsibilities, planning for the department’s future needs and operations, counselling employees on performance and contributing to employee pay decisions/changes. They may also lead a number of specialists to influence the operations of a department, in alignment with strategic as well as tactical priorities, while balancing short and long term goals and ensuring that budgets and schedules meet corporate requirements.
  • If the position has leadership responsibilities, People Leaders are expected to demonstrate a clear set of leadership behaviours to create an environment for colleagues to thrive and deliver to a consistently excellent standard. The four LEAD behaviours are:
    • L – Listen and be authentic
    • E – Energise and inspire
    • A – Align across the enterprise
    • D – Develop others
  • OR for an individual contributor, they will be a subject matter expert within own discipline and will guide technical direction. They will lead collaborative, multi-year assignments and guide team members through structured assignments, identify the need for the inclusion of other areas of specialisation to complete assignments. They will train, guide and coach less experienced specialists and provide information affecting long term profits, organisational risks and strategic decisions.
  • Advise key stakeholders, including functional leadership teams and senior management on functional and cross functional areas of impact and alignment.
  • Manage and mitigate risks through assessment, in support of the control and governance agenda.
  • Demonstrate leadership and accountability for managing risk and strengthening controls in relation to the work your team does.
  • Demonstrate comprehensive understanding of the organisation functions to contribute to achieving the goals of the business.
  • Collaborate with other areas of work, for business aligned support areas to keep up to speed with business activity and the business strategies.
  • Create solutions based on sophisticated analytical thought comparing and selecting complex alternatives. In-depth analysis with interpretative thinking will be required to define problems and develop innovative solutions.
  • Adopt and include the outcomes of extensive research in problem solving processes.
  • Seek out, build and maintain trusting relationships and partnerships with internal and external stakeholders in order to accomplish key business objectives, using influencing and negotiating skills to achieve outcomes.

Reasons to use Rodeo

I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?

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Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.

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Graduate Consultant — 2026 Scheme

PwC·London, UK
£35,000/yr

Why you're a good match

Strong

Your economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.

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Why you're a good match

You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.

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Strong

Experience fit

Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.

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Barclays Values and Mindset

All colleagues will be expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence and Stewardship – our moral compass, helping us do what we believe is right. They will also be expected to demonstrate the Barclays Mindset – to Empower, Challenge and Drive – the operating manual for how we behave.

Join Our Team

Join us as a Liquid Financing Data Engineer and become part of our Liquid Financing Technology team. You will help create and enhance data solutions that enable colleagues across Prime Services to better understand risk, access meaningful information, and respond to changing business needs.

In this role, you will support a modern cross-asset Client Risk platform used by Front Office teams. Working closely with colleagues across Business, Risk, Finance, Operations, and Technology, you will help improve how data is sourced, organised, and made available, ensuring users have access to timely and reliable information.

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You will support tools and capabilities that enable teams to monitor exposures, explore potential market scenarios, assess risk, and meet regulatory requirements. Your work will help improve an important platform used across the organisation, ensuring colleagues have access to trusted information that supports informed choices and positive outcomes for clients and teams.

This is an opportunity to work with a broad network of stakeholders across the business and support the ongoing development of data capabilities within a changing environment. You will play an important role in helping teams access the information they need to support day-to-day activities across the Prime Services business.

Essential Skills

To be successful as a Liquid Financing Data Engineer, you must have the following essential skills:

  • Extensive knowledge of the Prime Brokerage or Prime Services environment, including Synthetic and Cash Financing, Exchange Traded Derivatives, and OTC Derivatives across Equities, Credit, and Rates products.
  • In-depth knowledge of risk and governance practices, including margin methodologies, collateral valuation, exposure measurement, and P&L interpretation.
  • The ability to partner with Front Office, Product, Risk, and Technology teams to understand a broad range of business needs and translate them into practical data and technology solutions.
  • Experience supporting business and technology programmes, coordinating activity across multiple teams, and building positive working relationships with a wide range of stakeholders.

Highly Valued Skills

  • Knowledge of market risk concepts such as VaR, stress testing, Greeks, and exposure insights.
  • Familiarity with cloud and data technologies such as AWS, Snowflake, Databricks, or similar platforms.
  • Proficiency in using Python, Tableau, Qlik Sense, Power BI, or similar tools to work with large datasets, identify trends, and present information in a clear and accessible way.

Assessment

You may be assessed on the key critical skills relevant for success in role, such as risk and controls, change and transformation, business acumen, strategic thinking and digital and technology, as well as job-specific technical skills.

Location

This role will be based in London.

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Skills

Prime Brokerage
Synthetic Financing
Cash Financing
Exchange Traded Derivatives
OTC Derivatives
Risk Management
Data Pipelines
Machine Learning
Statistical Modeling
Python
Data Analysis
Stakeholder Management
Governance
Margin Methodologies
Collateral Valuation
Financial Reporting

Location

London, England, United Kingdom

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