Senior Data Architect

Thomson Keene; Greater London; On-site; GBP 110,000 - 160,000; Full time

Job summary

Thomson Keene is seeking a VP-level Data Architect to shape the enterprise data architecture across more than 30 platforms within a major financial institution. This strategic role focuses on front-to-back data governance, modelling and real-time risk capabilities across trading lifecycle.

You’ll define architecture and modelling standards, partner with senior stakeholders, and drive opportunities to improve data ecosystems in a predominantly non-engineering capacity.

Qualifications

• Experience in data architecture and data modelling at VP level or equivalent.
• Strong understanding of financial markets and end-to-end trade lifecycle.
• Experience driving enterprise data models across multiple platforms.

Responsibilities

• Define enterprise data architecture across markets business.
• Develop robust data models for trading and risk use cases.
• Establish architectural and modelling best practices across platforms.
• Challenge existing approaches and identify opportunities for improvement.
• Develop and present compelling business cases for architectural decisions.
• Collaborate with senior stakeholders across Markets, Data, Technology and Risk.
• Standardize approaches to trading data across multiple platforms.

Skills

Data architecture

Data modelling

Stakeholder management

Financial markets knowledge

Strategic thinking

Tools

AWS

Architecture tools

Job description

An exciting opportunity has arisen for a VP-level Data Architect to join a major financial institution's Chief Data & Analytics Office, working on a strategic programme that is shaping how trading data is modelled, governed and consumed across the organisation.

This is a strategic data architecture role, not a hands-on engineering position. The ideal candidate will combine deep financial markets knowledge with strong data architecture and modelling experience.

The Role

You’ll play a key role in building the enterprise data architecture that supports 30+ platforms across financial markets, helping create a consistent data foundation across the trading lifecycle.

The programme is focused on connecting front office / pre-trade, trade capture and post-trade data, enabling faster and more effective real-time risk capabilities.

You’ll be responsible for helping define the architecture, standards and modelling approaches that underpin this data ecosystem.

What We're Looking For

Front Office Financial Markets experience is essential.

We're particularly interested in candidates with backgrounds across:

• Credit
• Rates
• FX
• Equities
• Commodities

You should have a strong understanding of financial markets and the end-to-end trade lifecycle, combined with experience in data architecture and/or data modelling at VP level or equivalent.

You’ll ideally bring experience across:

• Architecture and modelling tools
• Data governance
• AWS or cloud environments (desirable, not essential)

What You’ll Be Doing

• Define and drive strategic data architecture across the markets business
• Develop robust enterprise data models that support trading and risk use cases
• Establish architectural and modelling best practice
• Challenge existing approaches and identify opportunities for improvement
• Develop and present compelling business cases for architectural and modelling decisions
• Work closely with senior stakeholders across Markets, Data, Technology and Risk
• Help establish consistent approaches to trading data across multiple platforms

The Ideal Candidate

You’ll be someone who can bridge the gap between financial markets and data architecture.

You don't need to be a hands-on coder or data engineer. What's important is that you understand how markets operate, how trades flow through the bank, and how those processes translate into effective enterprise data models and architecture.

You’ll be comfortable operating strategically, influencing senior stakeholders and challenging established thinking while bringing a strong understanding of markets to architectural decisions.