VP Data Platform Engineer — Real-Time Analytics

United States Digital Space LLC; Greater London; On-site; GBP 120,000 - 180,000; Full time

Benefits offered by this job

Best-In-Class BenefitsHealthcare &

Medical Insurance

Global career opportunities

Job summary

Goldman Sachs London is seeking a senior data platform engineer to own core post-trade systems, drive full product lifecycle, and deliver scalable, low-latency data processing. You will shape ingestion, distributed computation, and AI-augmented analytics while aligning with regulatory requirements and business needs.

The role emphasizes ownership, modern tech adaptation, and high standards for software quality within a bustling trading floor environment.

Qualifications

• About 5-10 years of professional experience developing high performance, low latency systems ( sub-seconds )
• Ability to contribute & drive on complex industrial scale development of systems independently
• Thorough knowledge of Java programming concepts
• Strong knowledge of object oriented programming, data structures, algorithms and design patterns
• Experience in Developing High Available, Low Latency systems with low foot-print – awareness of JVM internals, performance optimizations, concurrency, tuning for low-latency, GC-free real-time operation
• Experience in Distributed, Stream processing systems handling large volume ( big data ) in near real-time
• Exposure to stack like HDFS/S3, SingleStore, Kafka/Streaming Message System, Flink/Distributed Processing, Java/Scala
• Strong communication skills and the ability to work in a team and at the same able to drive things independently
• Strong analytical and problem solving skills

Responsibilities

• Design, build and maintain a high-performance, high-availability, high-capacity, scalable, near real-time yet nimble and adaptive platform for processing & persisting high volumes of business critical data and distribute it to downstream applications post-trade processing.
• Develop highly reliable data ingestion processes to consume large volumes of data emitted by trading and market data systems.
• Design distributed computation infrastructure to run parallelized queries over large volumes of data.
• Design and develop an AI-powered UI/agent framework that delivers intelligent analytics and insights over the data we process and hold, enabling users to interrogate and derive value from large-scale datasets.
• Communication with business, client applications, Regulatory & Compliance teams about new feature requests, explanation of existing features etc.

Skills

Java programming concepts

OO programming

Data structures

Algorithms

Design patterns

JVM internals

Performance optimization

Concurrency

Low latency

Distributed processing

Kafka

Flink

HDFS/S3

SingleStore

Scala

Tools

Kafka/Streaming

Flink/Distributed Processing

Java/Scala

Job description

Goldman Sachs London is seeking a senior data platform engineer to own core post-trade systems, drive full product lifecycle, and deliver scalable, low-latency data processing. You will shape ingestion, distributed computation, and AI-augmented analytics while aligning with regulatory requirements and business needs.

The role emphasizes ownership, modern tech adaptation, and high standards for software quality within a bustling trading floor environment.