FUTURUS FINANCIAL RECRUITMENT LTD
Data Product Owner - Global Markets - Senior Director - London
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My client is looking for the following person. Please read the spec carefully.
STRATEGIC BUSINESS UNIT DESCRIPTION
The Quant Group is a global, cross-asset team that builds the software, analytics, data products and AI-enabled tooling that underpin the Global Markets business. The analytical software and data solutions developed by The Quant Group are widely used across the bank, helping Distribution to price trades and serve clients, Trading to manage risk, Structuring to identify new client opportunities, and Risk and Finance partners to improve transparency, governance and control. The team is split between international business centres, with this role based in London.
JOB PURPOSE
In this role, you will serve as Data Product Owner for Global Markets within The Quant Group. You will define and drive the strategic direction of data products across core Capital Markets domains such as client, trade, market and risk data; champion adoption of governed data and analytics products; and ensure that solutions align with business priorities, regulatory expectations and technology strategy. The role acts as the bridge between trading, risk, quant, distribution, data governance and technology teams, translating abstract business requirements into scalable, production-grade data, analytics and AI-enabled solutions.
KEY ACCOUNTABILITIES
Data Product Strategy and Commercial Value
- Define target-state data products and semantic layers for key Global Markets domains, including client, trade, market, position, risk and reference data.
- Identify use cases where governed data, analytics and automation can improve pricing, risk transparency, client engagement, revenue generation or cost reduction.
- Champion data-driven decision-making and self-service analytics across the group, ensuring products are usable, trusted and aligned with front-office workflows.
- Partner with stakeholders to shape differentiated internal and client-facing data insights where appropriate.
Stakeholder Management and Product Leadership
- Engage senior business stakeholders across Trading, Distribution, Structuring, Risk, Quants and Technology to understand data needs, business value and adoption barriers.
- Own and communicate the data product roadmap, translating strategic priorities into clear outcomes, milestones and measurable OKRs.
- Facilitate prioritisation of data initiatives based on business impact, risk transparency, regulatory readiness, client value and operational efficiency.
- Lead cross-functional delivery discussions and ensure alignment between business intent, data governance requirements and technology implementation.
Business Requirement Analysis and Technology Solutioning
- Translate core, abstract business requirements into actionable product requirements, data models, delivery backlogs and acceptance criteria.
- Collaborate with technology teams to select and shape appropriate technologies for scalable analytics, trading strategy development, tick or time-series data, workflow automation and AI/ML-enabled use cases.
- Prefer Databricks, Spark and modern lakehouse patterns for scalable analytics where suitable, while recognising transferable experience with Snowflake and other enterprise data platforms.
- Ensure delivery choices balance speed, maintainability, governance, lineage, security and production robustness.
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Data Modelling, Governance and Controls
- Work closely with technical and quant teams on domain data modelling, canonical views, silver-layer enterprise views, data catalogues, lineage, metadata and critical data elements.
- Lead the design on data schemas, data storage, query apis and front to back information flows
- Provide product-owner challenge to ensure data models are fit for business purpose, support cross-asset analytics, and can scale to production risk and trading workflows.
- Drive strong data governance practices, including data ownership, stewardship, quality controls, metadata management, lineage and controlled data sharing.
- Ensure compliance with the bank’s policies, standards, regulatory expectations and industry good practice.
Strategic Data Source Determination
- Identify, assess and recommend strategic internal and external data sources for business, analytics, risk and AI use cases.
- Oversee data-source selection and prioritisation, including clarity on ownership, quality, licensing, controls and downstream consumption patterns.
- Work with governance and technology partners to ensure strategic data sources are discoverable, well documented and suitable for enterprise use.
Analytics, AI and Agentic Strategy Prioritisation
- Prioritise data access, tooling and platform capabilities required to support advanced analytics, AI/ML, NLP, intelligent automation and agentic strategies for the group.
- Identify opportunities to deploy production-grade analytics and AI-enabled solutions that improve decision-making, risk transparency, operational efficiency and front-office productivity.
- Work with quants and engineering teams to turn analytical prototypes into robust production workflows, dashboards, APIs, semantic layers or automated controls.
- Promote responsible AI and model-aware delivery, ensuring appropriate governance, explainability, monitoring and control considerations are addressed.
CROSS-FUNCTIONAL RELATIONSHIPS
This role will involve close collaboration with trading desks, distribution, structuring, risk management, quantitative analysts, technology partners, data governance teams and relevant external data or technology vendors across Global Markets. The successful candidate will be expected to operate credibly with senior stakeholders while remaining sufficiently hands-on to shape practical delivery with engineering and quant teams.
COMPLIANCE REQUIREMENTS/RESPONSIBILITIES
As an employee of the bank, the incumbent must comply with all applicable and Line of Business policies, standards, guidelines and controls. The role is expected to promote sound data governance, appropriate data usage, platform controls and responsible deployment of analytics and AI-enabled capabilities.
AUTHORITIES/DECISION RIGHTS
- Authority to set and communicate priorities for data product development, enhancement and adoption within the agreed Quant Group and Global Markets strategy.
- Authority to make recommendations regarding strategic data sources, data-product design, semantic-layer priorities and technology selection.
- Authority to steer data governance practices within The Quant Group, including ownership, prioritisation, metadata, lineage and controls.
- Authority to challenge requirements, delivery approaches or platform choices where they do not meet business value, governance, scalability or production-readiness expectations.
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KNOWLEDGE AND SKILLS
We are seeking a highly motivated individual with strong interpersonal, analytical, product and technical leadership skills. The following attributes are a useful guide to the level of performance expected:
- Degree in a quantitative discipline, computer science, data science, engineering, mathematics, physics or related field; advanced degree preferred.
- Significant experience in data product ownership, data strategy, analytics, quant strategy, risk analytics or related roles within financial services, ideally Global Markets or Capital Markets.
- Strong understanding of capital-markets products and workflows across one or more of rates, equities, securities finance, FX, commodities, derivatives, risk or portfolio analytics.
- Demonstrated ability to lead cross-functional teams, manage senior stakeholders, define OKRs, shape roadmaps and deliver enterprise data or analytics products.
- Hands-on understanding of data technologies and modern analytics platforms, preferably Databricks/Spark and lakehouse patterns; Snowflake experience is relevant and transferable but Databricks experience is preferred.
- Experience with Python, SQL and production analytics workflows; familiarity with big-data engineering, Kafka, Power BI, dashboards, APIs or workflow automation would be advantageous.
- Experience in data modelling, semantic layers, canonical data views, data catalogues, data quality, lineage, metadata, critical data elements and data governance frameworks.
- Understanding of AI/ML, NLP, intelligent automation, agentic AI concepts or production-grade analytics, with the ability to distinguish credible business use cases from experimentation.
- Proven ability to translate abstract business problems into clear product requirements, technical options and delivery plans.
- Excellent communication, influencing and client/stakeholder engagement skills, with the ability to operate from executive-level strategy through to delivery detail.
- Genuine passion for data-driven innovation, practical problem-solving and building elegant, governed, scalable solutions for front-office and risk users.
WORKING CONDITIONS
- This role operates within a normal office environment in London, with regular interaction across global teams.
AGENTS NOTES
The skills marked in YELLOW are considered high value. Data modelling and Data abstraction abilities are paramount because managing and capturing data is the essence of this role. Salary up to £200k plus a generous bonus. I have placed the overwhelming majority of people into this quant team over the last 20 years and only one person has left in that time (after ten years!). So, it's clearly a great place to work. PLEASE read the spec carefully and concentrate on the skills highlighted in YELLOW. They are vital skills and without them I'm afraid no application will move forward. Sorry. I will reply to every applicant myself personally.
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