Software Engineer, EPIC Technology Services

Point72 is a leading global alternative investment firm that focuses on delivering superior returns through innovative investing strategies. As a Software Engineer in their Technology team, you will manage data architecture and pipeline strategies, ensuring high availability and performance of data systems while mentoring a team of data engineers.

Responsibilities:

• 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 technical direction to a team of data engineers
• Conduct design and code reviews, setting best practices for testing, documentation, and maintainability
• Partner with application engineering, product, and investment stakeholders to translate business needs into scalable data solutions
• Own delivery outcomes for the data roadmap, balancing near-term execution with long-term platform health

Requirements:

• 10+ years of experience in data engineering and data platform development, including ownership of large-scale production data systems
• Proven leadership experience mentoring data engineers and driving technical direction across teams
• Strong hands-on expertise with MongoDB, SQL-based data systems, and Databricks
• Deep experience designing, building, and refactoring robust ETL/ELT pipelines across diverse data sources
• Solid understanding of data architecture, data modeling, and modern data warehousing principles
• Experience building high-performance, low-latency data systems that support end-user products
• Familiarity integrating data platforms with C# and Node.js middleware, including application topography and caching strategies
• Demonstrated experience implementing data quality, observability, governance, and availability frameworks
• Strong engineering discipline, including clean and testable code, automated testing, Git-based workflows, Agile delivery, and excellent communication, with a strong sense of ownership and accountability
• Commitment to the highest ethical standards