data engineer in investment services

Point72 is a global alternative investment firm that seeks to deliver returns for investors through fundamental and systematic investing strategies across asset classes and geographies. Its AI/ML – Investment Services team develops AI solutions to transform business processes and enhance enterprise intelligence.

• Design and build scalable, high-performance backend systems for investment services and AI-driven applications, and own their end-to-end lifecycle;
• Build and operate data pipelines for batch and streaming workloads to ingest, transform, validate, and deliver data to models and downstream consumers;
• Integrate and productionize generative AI and large language model solutions, including model serving, embeddings, and API-based workflows;
• Implement and maintain microservices and APIs that expose data and model functionality with a focus on reliability, low latency, and security;
• Optimize system performance and resilience through monitoring, observability, capacity planning, and automated incident response;
• Lead cross-functional delivery of prototypes into production with data scientists, researchers, product owners, and operations teams;
• Build and maintain CI/CD pipelines, automated testing, and deployment practices;
• Mentor and coach engineers on backend and data engineering best practices, help grow engineering capability, and contribute to the technical roadmap;
• Collaborate with security, compliance, and infrastructure partners to integrate data governance, access controls, and operational controls into solutions.

• Bachelor’s degree in computer science, software engineering, or a related technical field;
• At least 5 years of professional software engineering experience focused on backend system engineering;
• Experience building production data pipelines or data engineering solutions for batch and streaming data;
• Experience developing or integrating generative AI and large language model solutions, including model serving, embedding pipelines, fine-tuning workflows, or production integration with model APIs;
• Strong programming skills in one or more backend languages such as Python, Java, or Go, with the ability to design maintainable code and services;
• Experience deploying and operating services on cloud and container platforms using Docker and container orchestration technologies;
• Experience building CI/CD pipelines, automated testing, and infrastructure-as-code for service deployments;
• Strong data skills including SQL, data modeling, and relational and non-relational data stores;
• Excellent verbal and written communication skills in English and the ability to collaborate with technical and non-technical stakeholders;
• Commitment to the highest ethical standards.

• Sports card;
• Private life insurance;
• Private medical and dental care, with vision allowance;
• Private pension scheme;
• Volunteer opportunities;
• Support for employee-led affinity groups representing women, people of color, and the LGBTQ+ community;
• Business travel accident insurance;
• Employee assistance program;
• Educational assistance reimbursement.