VP Data Platform Architect: Real-Time, Low-Latency

Goldman Sachs; Greater London; On-site; GBP 120,000 - 170,000; Full time

Job summary

Goldman Sachs is seeking a senior data platform engineer to own core post-trade services. You will architect and implement scalable, low-latency systems and work across business lines to deliver real-time analytics and insights.

You will collaborate with trading and data teams, ensure resilience and performance, and drive modernization of the data processing stack using Java/Scala, Kafka, Flink, and S3/HDFS. This role sits in a fast-paced, global environment.

Qualifications

• 5-10 years of experience building high performance, low latency systems.
• Ability to contribute and drive complex industrial scale development independently.
• Thorough knowledge of Java programming concepts and design patterns.

Responsibilities

• Design and maintain a high-performance, scalable platform for post-trade data processing.
• Develop reliable data ingestion processes for large data volumes from trading and market data systems.
• Design distributed computation infrastructure for parallelized queries over big data.
• Develop an AI-powered UI/agent framework delivering analytics and insights over datasets.
• Communicate feature requests and explanations to business, client applications, and compliance teams.

Skills

Java programming

OOP concepts

Data structures

Low latency

Distributed processing

Team collaboration

Analytical thinking

Tools

HDFS/S3

Kafka

Flink

SingleStore

JVM internals

GC tuning

Job description

Goldman Sachs is seeking a senior data platform engineer to own core post-trade services. You will architect and implement scalable, low-latency systems and work across business lines to deliver real-time analytics and insights.

You will collaborate with trading and data teams, ensure resilience and performance, and drive modernization of the data processing stack using Java/Scala, Kafka, Flink, and S3/HDFS. This role sits in a fast-paced, global environment.