VP Data Engineer

Overview

As VP Data Engineer, you will shape data infrastructure for a global investment bank. You’ll build scalable data pipelines and Snowflake-based solutions, collaborating with Market Data, Quant and Risk teams to support analytics, VaR and stress testing. You drive reliable, auditable data foundations for large-scale financial datasets, enabling risk-aware decision making across the business. This role sits at the intersection of data engineering and risk analytics, offering impact across critical finance domains and cross-functional collaboration.

Pay / Benefits

• hybrid work model
• competitive salary + bonus
• London location
• permanent role

Responsibilities

• Build and enhance scalable data pipelines and infrastructure
• Develop Python ETL/ELT pipelines and complex SQL models
• Design and optimise Snowflake data solutions
• Integrate and manage large-scale financial and historical data
• Identify and resolve data quality and data integrity issues
• Work closely with Data, Quant, Market Data and Risk teams
• Ensure data solutions are scalable, reliable and auditable

Key requirements

• Proven experience in a Data Engineering / Data Development role
• Strong hands-on experience with Snowflake
• Strong AWS, Python and SQL skills
• Experience working with large-scale financial, market or time-series data
• Exposure to market data, market risk or risk analytics highly beneficial
• Understanding of VaR, SVaR, sensitivities or stress testing advantageous
• Strong analytical and problem-solving skills
• Excellent communication and stakeholder management skills
• communication
• stakeholder management
• problem-solving
• Snowflake
• AWS
• Python

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