Data Support Engineer for Quant Traders

Stanford Black Limited; Greater London; On-site; GBP 55,000 - 75,000; Full time

Benefits offered by this job

Free breakfast and lunch

13% pension

Year-one guaranteed bonus

Private health

Job summary

Stanford Black Limited in London is seeking a Data Support Engineer to bridge data, technology and research. You will support Quant researchers and traders, navigate data platforms, resolve issues, and improve tooling and documentation.

This role emphasizes strong Python usage, data quality, and collaboration with Data Engineering to maintain critical datasets across the firm's data estate.

Qualifications

• Experience in Data Support or similar technical user-facing role.
• Strong Python skills with data libraries.
• Understanding of data systems, pipelines and APIs.
• Experience supporting researchers, quants or traders.
• Financial services or systematic trading experience.
• Familiarity with data quality and backfills.

Responsibilities

• Act as first point of contact for researchers and traders needing data access and tooling.
• Investigate data issues and coordinate with Data Engineers to drive resolution.
• Support users across data platforms, pipelines and APIs.
• Onboard new researchers, helping them understand available datasets.
• Manage requests through JIRA and track resolutions.
• Develop documentation for datasets, tooling and processes.
• Contribute to expanding data coverage with live data and backfills.
• Use Python to investigate issues and improve support workflows.
• Identify recurring problems and contribute to long-term improvements.

Skills

Python

Data analysis

Data workflows

Jira

Communication

Problem solving

Tools

JIRA

Data tooling

APIs

Job description

Stanford Black Limited in London is seeking a Data Support Engineer to bridge data, technology and research. You will support Quant researchers and traders, navigate data platforms, resolve issues, and improve tooling and documentation.

This role emphasizes strong Python usage, data quality, and collaboration with Data Engineering to maintain critical datasets across the firm's data estate.