AVP Data Engineer

McGregor Recruitment; Kentucky; Hybrid; USD 97,000 - 161,000; Full time

Job summary

McGregor Recruitment is seeking an AVP Data Engineer for a London-based role with hybrid working (3 days in office).

You'll lead data engineering initiatives, build scalable data pipelines using Snowflake, AWS, Python and SQL, and partner with Market Data, Quant and Risk teams on critical analytics.

The role focuses on financial time-series data, VaR/risk analytics exposure, and ensuring data quality, governance and auditable infrastructure across the enterprise.

Qualifications

• 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 is highly beneficial.

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

Data engineering

Data pipelines

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.