Data Engineer, Proprietary Research
Point72New York, NY$160k – $220kPosted 24 February 2026
Job Description
ABOUT PROPRIETARY RESEARCH
On our proprietary research team—Market Intelligence—you’ll partner with our investment professionals and Compliance team to uncover insights about companies, industries, and the broader economy through deep fundamental research and applying data science and engineering techniques to alternative data sets. You’ll work alongside a talented team with diverse skills, backgrounds, and perspectives. Our researchers, product managers, and data scientists and engineers work together to build compliant research products that answer the questions posed by our investment professionals. We look for other bright, motivated, and collaborative people to join our team and grow with us—more than 90% of the leaders in our group were promoted from within.
ROLE SUMMARY
Data Engineers on the Proprietary Research team design and build solutions that enable investment professionals to effortlessly, extract insights from large, complex compliance approved structured and unstructured data sets. As a member of our Data Engineering team, you will work closely with investment professionals, researchers, and data scientists to design, build, and launch robust end-to-end data pipelines and tools that that help extract the most value out of Point72’s data assets. In this role, you will:
Develop and support big data processing pipelines including but not limited to ingestion, transformation, and end-customer delivery
Build out cloud-based infrastructure using distributed techniques for other data engineers / data scientists / researchers
Be at the forefront of new technology developments with respect to the handling and processing of big data and conduct proof of concepts evaluations of new technologies
Build and support visualization and exploration capabilities around our big data sets
WHAT EXCITES YOU
Transforming large unstructured, data sets into valuable investment research inputs
Learning and working with industry-leading cloud-computing technologies
Speaking with experts both inside and outside the Firm to understand data needs and offerings
Fast-paced work environments that at times require switching gears to address the needs of the business
Working as part of a cross-functional team made up of investment, research, and compliance professionals
WHAT EXCITES US
Excellent attention to detail, organization, and project management skills
Superb business intuition and a solution orientated, methodological approach to problem solving
Ability to collaborate and build relationships across multiple business units within the Firm
People who “elevate the room” through their work ethic, curiosity, and solution-orientated attitude
Adherence to the highest ethical standards working closely with the Firm’s Compliance team
WHAT’S REQUIRED
Experience or demonstrated interest in big data technologies
3+ years of experience in Data Engineering or related field
Strong experience in Python Development
Experience with Spark or Scala
Ability to devise novel and innovative solutions to challenges
Knowledge of/experience with graph databases is a plus
WHAT SUCCESS LOOKS LIKE
Integrity – You demonstrate 100% commitment to the highest ethical standards
Ownership – You take charge of your work, uphold your commitments, and always do your best
Commerciality – You focus on what matters, ask necessary questions, and are diligent about not wasting time
Humility – You welcome and are receptive to feedback and learn from past mistakes
Adaptability – You can triage business needs and context switch quickly and efficiently
Admirability – You elevate the room through your work ethic, domain knowledge, and work product
WE TAKE CARE OF OUR PEOPLE
We invest in our people, their careers, their health, and their well-being. When you work here, we provide:
Fully paid health care benefits
Generous parental and family leave policies
Mental and physical wellness programs
Volunteer opportunities
Non-profit matching gift program ... (truncated, view full listing at source)
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