At a Glance
- Tasks: Lead the rebuild of our Electronic Trading data platform into a cloud-native, AI-first system.
- Company: Join Goldman Sachs, a leading global investment banking and securities firm.
- Benefits: Enjoy competitive salary, professional development, and a diverse, inclusive workplace.
- Other info: Collaborative environment with opportunities for mentorship and career growth.
- Why this job: Make a real impact on cutting-edge technology and shape the future of trading.
- Qualifications: 5-10 years in high-performance systems; strong Java skills; leadership experience.
The predicted salary is between 99000 - 121000 £ per year.
Description
The Equities Data Platform team is core to delivering real-time analytics and handling critical fiduciary functions for Goldman Sachs' Electronic Trading business across Equities and Listed Options.
If you're excited by the challenge of engineering systems that process massive volumes of business-critical data in real time, this is your opportunity to make a real impact.
As a senior contributor, you will be one of the senior engineers leading the platform, owning the architecture and delivery of a core system within the Equities Data Platform and driving it through the full product lifecycle – from requirements gathering and design, through implementation, testing, deployment and support.
Want to be part of a once-in-a-generation rebuild of the Electronic Trading Data Strategy?
This role sits at the heart of that transformation – reimagining our stack to be cloud-native and AI-first, giving you the chance to help re-architect our data infrastructure from the ground up and embed AI-first thinking into everything we build.
We're looking for someone who takes pride of ownership, embraces new technologies with curiosity, and holds themselves – and the team around them – to the highest standard of software quality.
You'll take on significant leadership responsibilities, working alongside our other senior engineers to mentor engineers at all levels and help shape the technical direction of the team.
Responsibilities
- Act as one of the technical leads on the ground-up rebuild of our Electronic Trading data infrastructure into a cloud-native, AI-first platform.
- Design, build, and maintain a high-performance, high-availability, high-capacity platform that processes and persists massive volumes of business-critical data in near real time, distributing it seamlessly to downstream Electronic Trading applications.
- Develop highly reliable, industrial-strength data ingestion pipelines to consume large volumes of data emitted by trading and market data systems.
- Design distributed computation infrastructure capable of running parallelized queries across huge datasets, at speed and at scale.
- Design and build a cutting-edge, AI-powered UI/agent framework that delivers intelligent analytics and insights over our data – empowering users to interrogate and unlock value from large-scale datasets.
- Partner closely with business stakeholders, client applications, and Regulatory & Compliance teams to shape new feature requests, influence roadmap priorities, and clearly communicate existing capabilities.
- Provide technical direction and formal mentorship to engineers at all levels, working with fellow senior engineers to raise the bar on engineering practices across the team.
- Required Qualifications & Skill-Sets
- Around 5–10 years of professional experience with experience building high-performance, low-latency systems (sub-second) – at Vice President level.
- Proven ability to drive complex, industrial-scale development independently, while also leading and developing engineers across the team.
- Thorough knowledge of Java programming concepts (and Python a plus).
- Strong grounding in object-oriented programming, data structures, algorithms, and design patterns.
- Experience building highly available, low-latency systems with a small footprint – including JVM internals, performance optimization, concurrency, and tuning for GC-free, real-time operation.
- Experience with distributed stream-processing systems handling large-scale (big data) volumes in near real time.
- Hands-on exposure to technologies such as HDFS/S3, Snowflake, Single Store, Kafka (or similar streaming systems), Flink (or similar distributed processing frameworks), and Java/Scala (Python optional).
- Excellent communication skills, with the ability to collaborate effectively across teams while independently driving initiatives forward, and the credibility to influence senior stakeholders and technical peers.
- Strong analytical and problem-solving mindset, with a passion for tackling hard technical challenges.
- Demonstrable experience mentoring engineers and helping set technical standards within a team.
- Why Join Us
This is a rare chance to be part of a once-in-a-generation rebuild – helping take our Electronic Trading data platform to be cloud-native and AI-first from the ground up.
You'll own and shape mission-critical infrastructure at scale, work at the cutting edge of AI-driven analytics and grow your influence as a technical leader – all while working alongside a talented group of senior engineers and a collaborative team that values innovation and craftsmanship
ABOUT GOLDMAN SACHS
At Goldman Sachs, we commit our people, capital and ideas to help our clients, shareholders and the communities we serve to grow.
Founded in 1869, we are a leading global investment banking, securities and investment management firm.
Headquartered in New York, we maintain offices around the world.
We believe who you are makes you better at what you do.
We're committed to fostering and advancing diversity and inclusion in our own workplace and beyond by ensuring every individual within our firm has a number of opportunities to grow professionally and personally, from our training and development opportunities and firmwide networks to benefits, wellness and personal finance offerings and mindfulness programs.
Learn more about our culture, benefits, and people at GS. com/careers.
We’re committed to finding reasonable accommodations for candidates with special needs or disabilities during our recruiting process.
Learn more: https://www. goldmansachs. com/careers/footer/disability-statement. html
© The Goldman Sachs Group, Inc., 2023. All rights reserved.
Goldman Sachs is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, national origin, age, veterans status, disability, or any other characteristic protected by applicable law.
Global Banking Markets - Software Engineer - Equities Data Platform Engineering - London - Vice President employer: Goldman Sachs
Goldman Sachs is an exceptional employer, offering a dynamic work environment where innovation and collaboration thrive. With a strong commitment to employee growth, the firm provides extensive training and development opportunities, alongside a diverse and inclusive culture that values every individual's contributions. Located in a global financial hub, employees benefit from engaging with top-tier professionals while managing a portfolio of EMEA Corporate clients, ensuring meaningful and impactful work in the field of credit risk analysis.
StudySmarter Expert Advice🤫
We think this is how you could land Global Banking Markets - Software Engineer - Equities Data Platform Engineering - London - Vice President
✨Join Local Tech Meetups
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We think you need these skills to ace Global Banking Markets - Software Engineer - Equities Data Platform Engineering - London - Vice President
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Goldman Sachs.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Goldman Sachs and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at Goldman Sachs
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Goldman Sachs uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.