Summary
✨ AI‑Generated
A specialized financial technology organization is hiring a data engineer to build reliable data platforms for AI and analytical applications. The role involves transforming complex datasets into usable resources and working closely with technical and research teams.
Highlights
Join a small expert team building data platforms that support AI, analytics, and research workflows with significant ownership and collaboration.
Description
Data Engineer - Markets & AI Data Platform
Canary Wharf - Hyrbid
We’re hiring a Data Engineer to join a specialist financial markets business building AI, quantitative research and data products for institutional investors.
The company operates in a highly specialised area of global macro and financial markets, working with some of the world’s leading hedge funds, asset managers, banks and professional investors.
This is a small, highly experienced and fast-moving team with a flat structure.
Engineers work closely with researchers, quants and product teams, with real ownership over what gets built and how.
The role
You’ll help build the core data platform powering:
• AI agents and research tools
• Quantitative models
• Market and economic analysis
• Internal and client-facing products
• Dashboards and APIs
You’ll work with a broad mix of market, economic, research, news and internal datasets, turning fragmented and often messy information into clean, reliable and model-ready data.
You’ll also help shape the wider data architecture, including:
• Production ETL/ELT pipelines
• Bronze, silver and gold data layers
• Data quality and validation
• Instrument and ticker mapping
• Metadata and lineage
• Monitoring and observability
• Entitlements and permissions
• APIs and structured datasets for downstream applications
What we’re looking for
Strong experience with:
• Python and SQL
• Production data engineering and ETL/ELT
• Modern cloud data platforms such as Azure, Databricks, Delta Lake or Snowflake
• Large, complex or time-series datasets
• Data quality, monitoring and reliability
• Designing clean datasets for downstream users, applications and models
Experience with financial market or ticker-level data, including technologies such as kdb+, would be a strong advantage.
Why this role?
This is a rare opportunity to work at the intersection of financial markets, AI, quantitative research and modern data engineering.
You won’t be joining a large infrastructure team with narrow responsibilities.
You’ll have direct exposure to the people consuming the data, significant technical ownership, and the opportunity to influence the foundations of a growing AI and quant platform.
Ideal for someone who wants to build rather than simply maintain.
