I am working with a Tier 1 multi-strategy global hedge fund that is hiring a Data Platform Analyst to join its London-based Data Engineering function, supporting the build-out of a firmwide data platform underpinning trading across global markets.
This is a high-impact individual contributor role, embedded directly within Data Engineering, sitting at the intersection of Front Office stakeholders and platform build-out. The position goes beyond traditional BA responsibilities, with ownership across data requirements, modelling, and delivery within a modern data architecture.
You will act as a core conduit between Portfolio Managers, global stakeholders, and engineering, contributing to how data is ingested, structured, and delivered across the firm.
What you’ll be working on
- Owning end-to-end data requirements across the platform lifecycle (ingestion, modelling, transformation, delivery)
- Acting as the interface between Front Office users and Data Engineering
- Translating complex, ambiguous business needs into structured technical specifications and data models
- Supporting onboarding of market and alternative datasets, including vendor integration challenges
- Driving data quality, reconciliation, and validation processes across multiple data sources
- Contributing to data modelling, schema design, and transformation logic
- Operating within a modern architecture including Data Mesh principles, data contracts, and governance frameworks
- Supporting large-scale initiatives including historical backfills, PoCs, and new data product delivery
- This is a greenfield-to-scale data platform build, with direct exposure to Data Engineering leadership and global stakeholders.
What they’re looking for
- 7–15 years’ experience in financial services (buy-side or trading environments preferred)
- Strong expertise in SQL and data modelling (schemas, normalization, performance optimisation)
- Deep experience working with market data across asset classes, including vendor integration and financial identifier mapping (ISIN, CUSIP, etc.)
- Strong understanding of data pipelines, data quality/reconciliation, and OLTP vs OLAP paradigms
- Technical background, with hands-on programming experience (Python, Java or similar) and prior experience in engineering or development roles
- Proven track record operating as a hybrid between engineering and business, shaping data products and requirements
- Experience working closely with Data Engineering teams on scalable data platforms (not just reporting environments)
- Strong stakeholder engagement skills, with daily interaction with Front Office users (PMs, trading teams)
- Experience leveraging AI tools (e.g. ChatGPT, Copilot, Claude) in a professional context is beneficial
Compensation
- Highly competitive base salary and discretionary bonus + benefits
- The hire is active, with strong intent to move quickly
I am working with a Tier 1 multi-strategy global hedge fund that is hiring a Data Platform Analyst to join its London-based Data Engineering function, supporting the build-out of a firmwide data platform underpinning trading across global markets.
This is a high-impact individual contributor role, embedded directly within Data Engineering, sitting at the intersection of Front Office stakeholders and platform build-out. The position goes beyond traditional BA responsibilities, with ownership across data requirements, modelling, and delivery within a modern data architecture.
You will act as a core conduit between Portfolio Managers, global stakeholders, and engineering, contributing to how data is ingested, structured, and delivered across the firm.
What you’ll be working on
- Owning end-to-end data requirements across the platform lifecycle (ingestion, modelling, transformation, delivery)
- Acting as the interface between Front Office users and Data Engineering
- Translating complex, ambiguous business needs into structured technical specifications and data models
- Supporting onboarding of market and alternative datasets, including vendor integration challenges
- Driving data quality, reconciliation, and validation processes across multiple data sources
- Contributing to data modelling, schema design, and transformation logic
- Operating within a modern architecture including Data Mesh principles, data contracts, and governance frameworks
- Supporting large-scale initiatives including historical backfills, PoCs, and new data product delivery
- This is a greenfield-to-scale data platform build, with direct exposure to Data Engineering leadership and global stakeholders.
What they’re looking for
- 7–15 years’ experience in financial services (buy-side or trading environments preferred)
- Strong expertise in SQL and data modelling (schemas, normalization, performance optimisation)
- Deep experience working with market data across asset classes, including vendor integration and financial identifier mapping (ISIN, CUSIP, etc.)
- Strong understanding of data pipelines, data quality/reconciliation, and OLTP vs OLAP paradigms
- Technical background, with hands-on programming experience (Python, Java or similar) and prior experience in engineering or development roles
- Proven track record operating as a hybrid between engineering and business, shaping data products and requirements
- Experience working closely with Data Engineering teams on scalable data platforms (not just reporting environments)
- Strong stakeholder engagement skills, with daily interaction with Front Office users (PMs, trading teams)
- Experience leveraging AI tools (e.g. ChatGPT, Copilot, Claude) in a professional context is beneficial
Compensation
- Highly competitive base salary and discretionary bonus + benefits
- The hire is active, with strong intent to move quickly
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