Staff Data Engineer

AI Futures has been retained by one of Europe’s most innovative, technology-led investment firms. With over €2 Billion in assets under management they are reshaping how equity research and portfolio decisions are made through data-driven intelligence and applied AI.

At the heart of this transformation is data. You will design and scale the core data and AI infrastructure powering next-generation investment insights combining real-time data pipelines, retrieval-augmented generation (RAG), and large language models (LLMs) into a single intelligent research platform.

Working closely with top data scientists, engineers, and investors, you will help build the systems that transform billions of data points into actionable market intelligence, leveraging AWS, Databricks, and MLOps to do it at scale.

Base Salary: €120-160k + Bonus

The Role

• Design, implement, and optimize high-performance data pipelines (ETL/ELT) to process both structured and unstructured data at scale.
• Build and integrate AI-driven data workflows, including RAG pipelines, document intelligence, and LLM-based summarization and search.
• Partner with quant researchers, data scientists, and portfolio managers to turn raw data into actionable investment insights.
• Contribute to the architecture and automation of a modern data platform using AWS, Databricks, Terraform, and CI/CD pipelines.
• Play a key role in evolving the firm’s AI research infrastructure, combining engineering rigor with applied innovation.

Your Profile

• Deep experience in Python (Pandas, NumPy, FastAPI, Flask, Django).
• Strong knowledge of data pipelines and workflow orchestration tools (Airflow).
• Solid experience with Databricks, Snowflake, and modern Delta Lake architectures.
• Proven capability in AWS, Terraform, Docker, Kubernetes, and DevOps automation.
• Interest or hands‑on exposure to AI/LLM engineering – e.g., RAG systems, model integration, LLMOps, or vector databases.

Additional Assets Include

• Familiarity with financial or market data, especially within quantitative finance, asset management, or equity research.
• Exposure to ML model deployment (transformers, CNNs, embeddings, or NLP workflows).
• Familiarity with financial datasets and metrics (revenues, margins, cash flow statements) highly advantageous.

If you are a seasoned Data Engineer with deep coding ability, infrastructure expertise, and interest in AI + finance, I would welcome a confidential conversation to explore this opportunity further.

Seniority level

Mid‑Senior level

Employment type

Full-time

Industries

Financial Services and Investment Management