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- Tasks: Build scalable data pipelines and support AI-driven investment solutions.
- Company: Elite AI team in quantitative finance with a collaborative culture.
- Benefits: Competitive salary, performance bonuses, smart offices, and free food.
- Why this job: Make a real impact by transforming decision-making with cutting-edge technology.
- Qualifications: Experience in data processing, modern programming languages, and strong collaboration skills.
- Other info: Dynamic environment with constant learning and direct exposure to investment teams.
The predicted salary is between 36000 - 60000 £ per year.
My client is looking for an ambitious and highly motivated Data Engineer to join a lean, elite AI team operating at the intersection of quantitative finance and cutting-edge technology. In this role, you will act as a strategic partner to investment teams, helping to transform their decision-making processes by building scalable data architectures for Generative AI. This is an embedded position where you will sit directly with the teams you support, gaining first-hand insight into their workflows. You will be responsible for bridging the gap between raw financial data and the firm’s GenAI platform, ensuring models are fed by robust, high-performance data pipelines.
Responsibilities:
- Designing and building robust, scalable data pipelines and specialized workflows to power AI-driven investment solutions.
- Embedding within investment teams to identify opportunities for AI integration, translating complex data challenges into technical realities.
- Developing and promoting best practices for data engineering in an AI context, including the creation of shared libraries and feature stores.
- Ensuring tangible impact by delivering systems that allow teams to maintain and utilize AI tools autonomously after the initial embedding phase.
- Monitoring and optimizing AI data flows, ensuring the reliability and performance of existing systems while identifying enhancements for the core AI platform.
Requirements:
- Broad technical expertise in data processing and a passion for staying current with the rapidly evolving Generative AI landscape.
- A track record of high-value automation, with the ability to identify where data-driven AI can significantly improve business efficiency.
- Exceptional interpersonal skills, with a proven ability to collaborate with both technical engineers and non-technical investment professionals.
- A methodical approach to problem-solving, particularly when debugging complex, non-deterministic AI data outputs.
- Proficiency in modern languages such as Python, C#, Scala, Java, or Go.
- Experience with data storage and manipulation tools including SQL, Pandas/Polars, Snowflake, and Vector Databases.
- Familiarity with the GenAI ecosystem, including frameworks like LangChain or LlamaIndex and model evaluation tools like MLFlow.
- Knowledge of infrastructure and orchestration, specifically Docker, Kubernetes, and data tools like Airflow, Dagster, or DBT.
Competitive salary and performance-based bonus opportunities. A collaborative, flat structure with a culture of constant learning and modern tech. Direct exposure to the front-office environment and the firm’s bottom line. Smart offices, free food, and a commitment to professional skill development.
Data Engineer - Quant Trading employer: Acquire Me
Contact Detail:
Acquire Me Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer - Quant Trading
✨Tip Number 1
Network like a pro! Get out there and connect with folks in the industry. Attend meetups, webinars, or even just grab a coffee with someone who’s already in the game. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data engineering projects, especially those related to AI and finance. This is your chance to demonstrate how you can bridge the gap between raw data and actionable insights, making you stand out to potential employers.
✨Tip Number 3
Don’t just apply blindly! Tailor your approach for each role. Research the company and its culture, and make sure to highlight how your experience aligns with their needs. When you apply through our website, it shows you’re genuinely interested in being part of our team.
✨Tip Number 4
Prepare for interviews by brushing up on your technical skills and problem-solving techniques. Be ready to discuss your experience with data pipelines and AI integration. Remember, it’s not just about what you know, but how you communicate your ideas and collaborate with others.
We think you need these skills to ace Data Engineer - Quant Trading
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Data Engineer role. Highlight your expertise in data processing, automation, and any relevant projects you've worked on that showcase your ability to bridge the gap between raw data and AI solutions.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about the intersection of quantitative finance and AI. Share specific examples of how you've tackled complex data challenges and how you can contribute to our elite team at StudySmarter.
Showcase Your Technical Skills: Don’t shy away from listing your proficiency in programming languages like Python or Java, and tools like SQL or Snowflake. We want to see your technical prowess, so include any relevant certifications or projects that demonstrate your capabilities in building scalable data architectures.
Apply Through Our Website: We encourage you to apply directly through our website for a smoother application process. This way, we can easily track your application and ensure it gets the attention it deserves. Plus, it shows us you're keen on joining our team!
How to prepare for a job interview at Acquire Me
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technical skills listed in the job description. Brush up on your Python, SQL, and any other relevant languages or tools. Be ready to discuss specific projects where you've used these technologies to solve real-world problems.
✨Understand the Business Context
Since this role is embedded within investment teams, it’s crucial to grasp how data engineering impacts decision-making in finance. Research the company’s approach to AI in trading and think about how you can contribute to their goals. This will show your genuine interest and strategic thinking.
✨Prepare for Problem-Solving Questions
Expect to tackle some complex, non-deterministic problems during the interview. Practice explaining your thought process clearly and methodically. Use examples from your past experiences where you successfully debugged or optimised data flows, as this will demonstrate your analytical skills.
✨Showcase Your Collaboration Skills
This role requires working closely with both technical and non-technical teams. Prepare examples that highlight your interpersonal skills and ability to communicate complex ideas simply. Think of times when you’ve bridged gaps between different stakeholders to achieve a common goal.