Data Engineer, Proprietary Research
At a glance
Mid-level Data Engineering role at Point72. New York · full-time · $160,000–$220,000 base.
dataroles summary, based on the employer's posting.
What you'll do
- Build and maintain pipelines that ingest, transform, and deliver large structured and unstructured datasets
- Create cloud infrastructure with distributed techniques for data engineers, data scientists, and researchers
- Evaluate emerging big-data technologies through proof-of-concept work
- Develop tools that help users explore and visualize large datasets
What you bring
- At least three years in data engineering or a related area
- Strong Python development skills, plus experience with Spark or Scala
- Experience with, or demonstrated interest in, big-data technologies
- You bring a methodical approach to solving problems and can devise new solutions
Who this fits
This role suits a mid-level data engineer who wants to turn complex datasets into inputs for investment research. You’ll work with investment professionals, researchers, data scientists, and Compliance colleagues, and need to adapt as business needs shift. The position is based in New York.
From the employer
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
- Support for employee-led affinity groups representing women, minorities and the LGBTQ+ community
- Tuition assistance
- A 401(k) savings program with an employer match and more
ABOUT POINT72
Point72 is a leading global alternative investment firm led by Steven A. Cohen. Building on more than 30 years of investing experience, Point72 seeks to deliver superior returns for its investors through fundamental and systematic investing strategies across asset classes and geographies. We aim to attract and retain the industry’s brightest talent by cultivating an investor-led culture and committing to our people’s long-term growth. For more information, visit www.Point72.com/about.
The annual base salary range for this role is $160,000-$220,000, which does not include discretionary bonus compensation or our comprehensive benefits package. Actual compensation offered to the successful candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level, among other things.
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