Data Engineer – Quant Trading

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.

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