Equities Quant Engineer: Data Pipelines & Analytics

StreetID

New York (NY)

On-site

USD 140,000 - 180,000

Full time

6 days ago
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Job summary

StreetID in New York is seeking an Equities Quant Engineer to bridge data engineering, analytics, and storage for investment teams. You will build scalable pipelines and contribute to data-driven investment insights, collaborating with finance and IR stakeholders.

The role emphasizes data quality, rapid iteration, and close interaction with quant analysts and developers in a fast-paced equities environment.

Qualifications

  • Requires a Bachelor’s degree in CS, Finance, or related field.
  • Experience in data engineering, data analysis, or software development.
  • Proficient with SQL and relational databases (PostgreSQL preferred; others also relevant).
  • Familiar with Python, R, Java, or Scala.
  • Ability to write, understand, and troubleshoot complex SQL.

Responsibilities

  • Analyze large datasets to uncover trends and insights that can support investment decisions.
  • Work with investment, finance, and investor relations teams to understand data requirements and build solutions.
  • Maintain data quality, accuracy, and consistency across data sources and applications.
  • Design, develop, and maintain data pipelines, ETL processes, and data storage solutions.
  • Improve processes and systems to increase efficiency and effectiveness.

Skills

Data analysis
Data engineering
Software development

Education

Bachelor's degree in Computer Science, Finance, or a related field

Tools

PostgreSQL
MS SQL Server
Oracle
Python
R
Java
Scala
SQL

Job description

StreetID in New York is seeking an Equities Quant Engineer to bridge data engineering, analytics, and storage for investment teams. You will build scalable pipelines and contribute to data-driven investment insights, collaborating with finance and IR stakeholders.

The role emphasizes data quality, rapid iteration, and close interaction with quant analysts and developers in a fast-paced equities environment.

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