VP Data Engineer

McGregor Recruitment; Greater London; Hybrid; GBP 90,000 - 150,000; Full time

Job summary

McGregor Recruitment is seeking a VP Data Engineer in London with hybrid working arrangement (3 days in the office). You will join a global financial technology environment to build and enhance critical data infrastructure across the business.

You will work with Snowflake, AWS, Python and SQL on large-scale financial and historical data, collaborating with Market Data, Quant and Risk teams to support analytics, VaR and stress testing.

Qualifications

• Proven experience in a Data Engineering role.
• Hands-on Snowflake experience.
• Strong AWS, Python and SQL skills.
• Experience with large-scale financial, market or time-series data.
• Exposure to market data or risk analytics is beneficial.
• Understanding VaR, SVaR and stress testing is advantageous.

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.

Skills

Data pipelines

Stakeholder management

Analytics

Communication

Problem solving

Tools

Snowflake

AWS

Python

SQL

Job description

VP Data Engineer

Financial Technology

Location: London

Working: Hybrid (3 days/week in office)

Salary: Up to £150k + bonus

The Role

• Joining a global investment bank as part of a growing Data Engineering function, working on critical data infrastructure across the business.
• You’ll build and enhance modern data solutions using Snowflake, AWS, Python and SQL, working with large-scale financial and historical data.
• The role sits closely with Market Data, Quant and Risk teams, with your work supporting areas including market risk analytics, VaR and stress testing.

Key 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 concepts such as VaR, SVaR, sensitivities or stress testing advantageous
• Strong analytical and problem-solving skills
• Excellent communication and stakeholder management skills

No sponsorship available.