Senior Data Engineer, Proprietary Research

About this job

Point72 is a prominent global alternative investment firm that combines fundamental and systematic strategies. Within its Proprietary Research team, known as Market Intelligence, professionals collaborate closely with investment experts and compliance specialists to generate deep economic and company insights using data science and engineering on alternative datasets. As a Senior Data Engineer on this team, your everyday responsibilities involve designing and constructing the Data and AI Platform. You will transform complex structured and unstructured information into actionable insights by building robust big data pipelines, developing reusable software libraries, and implementing data governance controls. You will also work alongside product managers, industry researchers, and data scientists to create compliant research products, deploy AI-native cloud infrastructure, and utilize modern tools like LLMs and agentic workflows to support business needs.

Responsibilities

• Design and build big data pipelines for data ingestion, transformation, and delivery of AI-ready assets.
• Develop reusable software components, libraries, and APIs for experimentation and production.
• Implement data quality, lineage, and governance controls to ensure reliability and compliance.
• Build scalable, AI-native, cloud-based infrastructure using distributed systems and modern cloud technologies.
• Optimize system performance, cost, and reliability through benchmarking and continuous improvements.
• Explore emerging data and AI technologies, executing proof of concepts into business deliverables.
• Collaborate with investment, research, data science, and compliance teams to create production-ready data products.
• Provide hands-on technical leadership and influence architecture across engineers and stakeholders.

Requirements

• 5+ years of experience in Data Engineering, Software Engineering, or a related field.
• 2+ years of strong hands-on Python development experience.
• Experience in system design and leading development efforts involving multiple contributors.
• Strong knowledge of distributed data processing frameworks such as Spark.
• Experience building scalable APIs, backend infrastructure, and software applications.
• Hands-on experience with cloud platforms for data storage and compute like AWS, GCP, or Azure.
• Experience with workflow orchestration technologies such as Airflow.
• Commitment to the highest ethical standards and key values like integrity, ownership, and humility.

Good to have

• Exposure to LangGraph, LangChain, embedding models, vector databases, or graph databases.
• Strong interest in staying current with AI advancements and applying emerging techniques.

Who should apply

This role suits experienced data or software engineering professionals who possess a strong background in Python and distributed frameworks, and who are keen on applying modern AI, cloud infrastructure, and data pipeline technologies within the investment research sector. Candidates should exhibit strong project management abilities, collaboration skills, and a commitment to high ethical standards. The posting does not mention fresher eligibility, as it explicitly requires multiple years of specialized industry experience.

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