Systematic Investing Data Engineer

Legalandgeneral; Greater London; On-site; GBP 90,000 - 140,000; Full time

Benefits offered by this job

Annual bonus

Pension plan

Life assurance

Healthcare

Job summary

Legal & General in London is hiring a Systematic Index Strategist to join the Asset Management division. You will maintain research infrastructure, PostgreSQL databases, and data pipelines, partnering with investment researchers and the Technology & Analytics function to productionise tools.

Ideal candidates have strong Python, SQL, and quantitative finance knowledge, with a track record of building scalable data systems and backtesting frameworks to support equity and fixed income strategies.

Qualifications

• Strong Python programming and experience with large datasets and analytical frameworks.
• Experience with SQL and database management, ideally PostgreSQL.
• Knowledge of quantitative research techniques and systematic investing concepts.

Responsibilities

• Maintain and enhance the PostgreSQL database and research infrastructure.
• Develop data ingestion, validation and monitoring processes across data sources.
• Manage GitHub repositories and promote development best practices.
• Refactor and productionise research code into scalable analytical frameworks.
• Build and maintain Python libraries and automated workflows for research and portfolio analysis.
• Collaborate with Technology & Analytics to improve data processes and tooling.
• Support research and implementation of systematic investment strategies across markets.
• Perform quantitative analysis and backtesting using diverse datasets.

Skills

Python

SQL

PostgreSQL

Data analysis

Quantitative finance

Education

Bachelor's degree in a quantitative discipline

Tools

GitHub

Pandas

NumPy

Job description

Legal & General in London is hiring a Systematic Index Strategist to join the Asset Management division. You will maintain research infrastructure, PostgreSQL databases, and data pipelines, partnering with investment researchers and the Technology & Analytics function to productionise tools.

Ideal candidates have strong Python, SQL, and quantitative finance knowledge, with a track record of building scalable data systems and backtesting frameworks to support equity and fixed income strategies.