Software Engineer, EPIC Technology Services
Point72 Asset Management - New York
Posted Apr 2, 2026
Benefits
- Parental leave
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- Non-birth-parent leave
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- Family-building benefits
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- Fertility benefits: Not verified
- Adoption assistance: Not verified
- Surrogacy assistance: Not verified
- Mental health support
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- Relocation assistance
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- Childcare support
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- Learning budget
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- Verification
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- Salary
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- 401(k) match
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Schedule
- Shift type
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- Weekend work
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Application
- Cover letter
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- Assessment
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- Deadline
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Where they hire
State eligibility is not yet verified.
About this role
Software Engineer, EPIC Technology Services New York A Career with Point72's Technology Team As Point72 reimagines the future of investing, our Technology team is constantly evolving our firm's IT infrastructure and engineering capabilities, positioning us at the forefront of a rapidly evolving technology landscape. We're a team of experts who experiment and work to discover new ways to harness open-source solutions, modern cloud architectures, and sophisticated Artificial Intelligence (AI) solutions, while embracing enterprise agile methodologies. Our commitment to building and innovating in the AI space provides the framework intended to drive smarter decision making and enhance how we build and operate our platforms and applications. As a member of Point72's Technology team, we encourage and support your professional development from day one-helping you advance your technical skills, contribute innovative ideas, and satisfy your own intellectual curiosity-all while delivering real business impact for our multi-billion-dollar global business. What you'll do - Manage the end-to-end data architecture and pipeline strategy for the firm's research management platform. - Design and oversee data ingress pipelines supporting low latency, analyst facing research dashboards and data egress pipelines for downstream application, analytics, and AI consumption. - Ensure data pipelines meet high standards for availability, scalability, performance, and reliability. - Define and enforce modeling standards that support current and future research workflows. - Establish and maintain data governance practices, including lineage, cataloging, auditing, and access controls. - Ensure data platforms and structures are compatible with AI tooling, including MCP, agents, and automation. - Lead, mentor, and provide
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