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Here's a clear, concise summary of the VP Data Engineer role at McGregor Boyall, following the given rules and professional, neutral tone: --- **VP Data Engineer** McGregor Boyall **Job Title:** VP Data Engineer **Location:** London, London, WC2N 5DU, England, United Kingdom **Salary:** Up to £150k + bonus **Contract:** Permanent **Working Pattern:** Hybrid (3 days/week in office) **Job Reference:** b9674c47-3056-4f2a-969c-4d48d4a3d811 **Posted:** 17/09/2026 **Key Responsibilities:** - Build and enhance modern data solutions using Snowflake, AWS, Python, and SQL - Design and optimize data pipelines and infrastructure - Collaborate with Market Data, Quant, and Risk teams - Ensure data solutions are scalable, reliable, and auditable **Required Skills:** - Proven experience in a Data Engineering/Data Development role - Strong hands-on experience with Snowflake, AWS, Python, and SQL - Experience working with large-scale financial, market, or time-series data - Understanding of concepts such as VaR, SVaR, sensitivities, or stress testing is beneficial **Additional Information:** - No sponsorship available **How to Apply:** - Get in touch for more details – [ncarolan@mcgregor-boyall.com](mailto:ncarolan@mcgregor-boyall.com) **Recruitment Agency:** McGregor Boyall **Contact Information:** - Nathan Carolan
- Compensation
- £150,000 – £150,000 GBP
- City
- London
- Country
- United Kingdom
Currency: £ (GBP)
Full Job Description
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Job Details
VP Data Engineer
- 150000.00 - 150000.00 per annum
- London, London, WC2N 5DU, England, United Kingdom
- Permanent
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.
- Youll 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.
Get in touch for more details ncarolan@mcgregor-boyall.com
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