---
title: 'Reference Data Business Analyst at Qube Research & Technologies'
canonical: 'https://feeny.ai/job/reference-data-business-analyst-qube-research-technologies-london-8bab8hmxcsfg'
type: 'job'
last_seen: '2026-09-12'
---

# Reference Data Business Analyst at Qube Research & Technologies

- **Company:** Qube Research & Technologies
- **Location:** London, United Kingdom
- **Posted:** 2026-09-09
- **Last confirmed live:** 2026-09-12
- **Apply:** https://job-boards.greenhouse.io/quberesearchandtechnologies/jobs/8789177002

## Job description

QRT is a global quantitative and systematic investment manager, operating across all liquid asset classes. We are a data- and technology-driven organization applying scientific methods to investing. Our collaborative culture and focus on innovation enable us to solve complex challenges and deliver high-quality returns for our investors. The newly formed Reference Data Technology Team is building a new reference data system. The team works with stakeholders across Trading, Operations, Compliance and Research to translate business and regulatory requirements into data models, datasets and data quality controls.

## Your future role within QRT

We are seeking an exceptional Reference Data Business Analyst to join our Reference Data Technology Team. The role is expected to involve the following activities:

- Translate business and regulatory requirements into data entity models and datasets for the new reference data system.
- Work closely with the Data/Platform Architect to ensure business requirements map cleanly onto the technical model.
- Gather and validate requirements directly with domain stakeholders across Trading, Compliance and Research.
- Partner with Trading, Operations and Compliance teams to build automated data quality rules and checks, exception-management workflows and metrics.
- Provide day-to-day support to business, compliance and technology teams as a subject matter expert on data queries and system behaviour.
- Apply expert knowledge of equity reference data, related events, and the lifecycle and processing of corporate actions.
- Support the initial delivery focused on Equities and ETFs and its direct impact on the trading business.
- Produce data dictionaries, entity relationship diagrams and requirements specifications.

## Your present skillset

- Experience producing entity and data models for reference or master data platforms in financial services.
- Deep working knowledge of ETF reference data, including composition and basket data, creation and redemption mechanics, and identifiers.
- Hands-on knowledge of ETF corporate actions processing, including dividends, splits, mergers and delistings.
- Understanding of corporate actions lifecycle stages, timing and effective-date handling, and the downstream impact of processing errors.
- Experience defining corporate actions data quality rules, including the detection of missed or conflicting action records and effective-date validation.
- Strong requirements-gathering skills across multiple stakeholder groups, including Trading, Compliance and Operations.
- Working knowledge of data quality concepts, including completeness, accuracy, timeliness and referential integrity.
- Ability to translate regulatory and business rules into structured, testable data rules.
- Comfortable working directly with technical architects to map business requirements onto a reference data model.
- Strong written documentation skills, including data dictionaries, entity relationship diagrams and requirements specifications.
- Strong database and SQL skills for data interrogation and analysis.

Desirable to have experience or a willingness to learn in the following areas

- Client and account reference data, including legal entity structures, KYC, account hierarchies and LEIs.
- Master data management concepts, including golden source, survivorship and entity resolution.
- Scoping an MVP and maintaining a firm line on deferred scope.
- Data lineage, metadata cataloguing and associated tooling.
- Data modelling tools, including entity relationship diagramming and data catalogue tools.
- UK and EU financial services regulatory frameworks relevant to reference data, including the LEI regime and KYC/CDD requirements.
- Python experience and knowledge.

QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees achieve a healthy work-life balance.

## About Qube Research & Technologies

## Company Overview
- **One-liner**: Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager that deploys data, research, and technology to execute multi-strategy trading across all asset classes.
- **Entity Type**: Private (Privately Held)
- **Headquarters**: London, United Kingdom
- **Founded**: 2018 (spun off from a systematic trading team at Credit Suisse, with roots tracing to 2016)
- **Founders**: Not publicly disclosed (spun out of Credit Suisse's systematic trading team)

## Core Business
- **Primary industry**: Financial Services / Quantitative Hedge Fund / Systematic Investment Management
- **Target customers**: Institutional investors (pension funds, sovereign wealth funds, endowments, and other large allocators)
- **Mission/purpose**: To combine data, research, technology, and trading expertise to solve complex challenges and deliver high-quality returns for investors.

## Products & Services
- **Multi-Strategy Investment Management**: QRT deploys a diverse range of investment strategies across geographies, asset classes (equities, fixed income, FX, commodities, crypto), and time frames (high-frequency to long-term). They operate as a systematic, data-driven hedge fund.
- **Quantitative Research & Technology Platform**: The firm's core offering is its proprietary technology and research platform, which enables quantitative researchers, data scientists, and software engineers to develop and execute trading models at scale.

## Market Standing
- **Valuation/Market Cap**: Not disclosed (privately held)
- **Key Metric**: Total Funding: Not applicable (privately held, profitable firm). **Assets Under Management (AUM)**: Added $4bn in AUM between the start of 2024 and May 2024, returning 22% from January to April 2024 according to reports.
- **Notable Investors/Partners**: Institutional investors (pension funds, sovereign wealth funds, endowments). Spun off from Credit Suisse's systematic trading team.
- **Growth Signals**: Headcount grew **+56.4% YoY** to 1,787 employees. Expanded to 16 offices across 24 countries (including new offices in Dubai, Chicago, and New York). Over 100 active job openings. AUM grew significantly in 2024.

## Competitive Advantages
- **Data & Technology Moat**: Combines proprietary research, massive datasets, and advanced technology (including machine learning, low-latency C++/FPGA systems, and cloud infrastructure) to generate alpha across all asset classes and timeframes.
- **Multi-Strategy, Multi-Asset Diversification**: Operates across geographies, asset classes, and time horizons, reducing single-strategy risk and allowing capital to flow to the best opportunities.
- **Talent Density & Culture**: Rapidly hires top talent from competitors (Goldman Sachs, Citadel, Millennium, Credit Suisse) and top universities. A young, high-performance culture with 74% of staff aged 40 or under.
- **Compensation Model**: Over 40% of staff are part of a deferred compensation plan with exposure to fund performance, aligning employee incentives directly with investor returns.

## Strategic Focus
- **Aggressive Global Expansion**: Rapidly scaling headcount (+56% YoY) and opening new offices in key financial hubs (Dubai, Chicago, New York, Singapore, Hong Kong).
- **Technology & Infrastructure Investment**: Heavy investment in low-latency trading systems, FPGA engineering, cloud infrastructure, and data platforms (Snowflake, Python, C++, C#).
- **Talent Acquisition**: Prioritizing hiring top quantitative researchers, software engineers, data scientists, and traders from competitors and top universities. Over 100 open roles globally.
- **Crypto & New Asset Classes**: Actively building a crypto trading team and expanding into new asset classes and geographies.

## Why Work Here
- **Compensation & Career Growth**: Highly competitive pay. Interns can earn around $12k per month. Over 40% of staff are in a deferred compensation plan with exposure to fund performance. Glassdoor rating of 4.1/5.0, with compensation (4.0) and career opportunities (4.1) as top highlights.
- **Culture & Demographics**: Young, high-performance culture (74% of staff aged 40 or under, 38% aged 30 or under). 90% of staff reported good team morale in an internal survey. Described as a "fertile ground for experimental research."
- **Work Environment**: Hybrid/office-based depending on role and location. Offices in London (HQ), Paris, Hong Kong, Singapore, New York, Chicago, Dubai, Mumbai, Geneva, and more. New London office in Victoria.
- **Notable Perks**: Deferred compensation plan with fund performance exposure. Interns can earn around $12k per month. Strong focus on work-life balance initiatives.
- **Engineering Culture**: Heavy emphasis on technology (Python, C++, C#, Snowflake, FPGA, low-latency systems, MLflow, Kubernetes). 22% of staff are in Research roles, 6% in Technical roles. Strong support for coding initiatives and academic projects in maths and science.

## Sources
1. [qube-rt.com](https://www.qube-rt.com/)
2. [LinkedIn](https://www.linkedin.com/company/qube-rt)
3. [efinancialcareers-canada.com](https://www.efinancialcareers-canada.com/news/qube-research-and-technologies-hiring-and-culture)
4. [Greenhouse Job Board](http://job-boards.greenhouse.io/quberesearchandtechnologies?page=2)
5. [Careers Page](https://www.qube-rt.com/careers)

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