AVP Data Engineer

Mcgregor Boyall; Greater London; Hybrid; GBP 72,000 - 120,000; Full time

Job summary

Mcgregor Boyall is seeking an AVP Data Engineer in London for a hybrid role, requiring three days in the office. You will join a global investment bank to build and enhance critical data infrastructure and modern data pipelines using Snowflake, AWS, Python and SQL.

The role emphasizes market data, risk analytics and time-series data, delivering scalable, auditable solutions and collaborating with Market Data, Quant and Risk teams for risk analytics and VaR-related work.

Qualifications

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

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

Snowflake

AWS

Python

SQL

Market Data

Risk Analytics

Job description

AVP Data Engineer

Financial Technology

Location: London

Working: Hybrid (3 days/week in office)

Salary: Up to £120k + 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.