Job Detail

Data Engineer

Title
Data Engineer
Type
Full-time
Primary Location
Philadelphia
Education
Bachelor's Degree
Rate Type
Per hour
Job Description

Do you love building and pioneering in the technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? Most importantly, do you love experimenting with new technologies and increasing your knowledge of the data space?

We are looking for a seasoned data engineer who can work with a leading hedge fund in Philadelphia. They are constantly receiving new data sources that need to be integrated and fed to the appropriate lines of business as soon as possible. The team is expected to turn around a new pipeline for a new source within 1-2 days and needs a leader who can help not only with the low-level work but one who can make the process more efficient.

Remote work until the end of the virus then location in central Philidelphia.

What you will do:

  • Lead a small team responsible for providing best in class data services to multiple internal stakeholders including Investment and Quantitative Research, Investment Analysis, and Technology
  • Build large-scale batch and real-time data pipelines for alternative data
  • Quickly build new pipelines for new data sources
  • Integration of alternative data with traditional data sources
  • Define the roadmap and drive execution
  • Drive the data practice to continuously become more efficient
  • Share your passion for staying on top of tech trends, experimenting with and learning new technologies, participating in internal & external technology communities, and mentoring other members of the engineering community
#LI-TS1
Job Requirements
  • Experience consuming bespoke data sets with no control over the format of the data
  • Excellent knowledge of tooling in the data space and the ability to hone in on the right stack for the problem
  • Demonstrated experience in large dataset design and modeling
  • Demonstrated expertise in data engineering, including but not limited to data platforms, ETL process engineering, data quality monitoring, and machine-assisted data discovery
  • Familiarity with NoSQL technologies, such as key/value store, columnar store, document store, etc.
  • Well-versed in the features of popular Big Data solutions, including cloud-hosted platforms
  • Proficiency in a diverse set of programming languages, such as C# (.NET) and Python
  • Experience working with Redshift and SQL Server
  • Working knowledge of Docker and Kubernetes
  • Effectively manage expectations
  • Ability to mentor junior data engineers
  • Minimum Bachelor’s degree in Computer Science or Computer Engineering
  • Must have strong coding skills and be capable of creating a new pipeline based on a new data source quickly (max 1-2 days).

Prospect 33 is an equal opportunity employer.

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