Point72

Data Engineer, Market Intelligence

Point72
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7 months ago
Warsaw, PolandMid Level

Responsibilities

  • Develop and support big data processing pipelines covering ingestion, transformation, and end-customer delivery.
  • Build cloud-based infrastructure using distributed techniques for data engineers, data scientists, and researchers.
  • Evaluate emerging technologies for handling and processing big data through proof-of-concept projects.
  • Build and support visualization and exploration capabilities for large data sets.
  • Collaborate with investment professionals, researchers, data scientists, and compliance teams to develop compliant research products.

Requirements

  • Have experience or demonstrated interest in big data technologies.
  • Have 3+ years of experience in data engineering or a related field.
  • Have strong Python development experience.
  • Have experience with Spark or Scala.
  • Be able to devise novel and innovative solutions to challenges.
  • Experience with graph databases is a plus.

Benefits

  • Sports card.
  • Private life insurance.
  • Private medical and dental care with a vision allowance.
  • Private pension scheme.
  • Volunteer opportunities.
  • Support for employee-led affinity groups representing women, people of color, and the LGBTQ+ community.
  • Business travel accident insurance.
  • Employee assistance program.
  • Educational assistance reimbursement.
  • The role is based in Point72’s Warsaw office.

Tech Stack

Categories

Data Engineering
Point72

About Point72

1,001-5,000 employees

Point72 is a global alternative investment firm that deploys fundamental and systematic strategies across equities and other asset classes for institutional and qualified investors. The firm earns management and performance fees and also invests partner capital. Founded in 2014 by Steven A. Cohen and headquartered in Stamford, Connecticut, it operates a multi-manager platform with offices worldwide and a large in-house technology organization supporting research, trading, data, and risk.

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