The Fixed Income & Commodities Data team is looking for a Data Engineer (4+ years of experience) who will work on the acquisition, accessibility, normalizing, and cataloging of large sets of data.

Responsibilities:

• Create and maintain optimal data pipeline architecture.

• Extract, transform, and load data from a wide variety of data sources using Python and SQL.

• Provide users access to datasets using REST and Python APIs.

• Categorize, catalog, cleanse, and normalize datasets.

• Communicate effectively with business users and technology stakeholders.

Required skills/experience:

• 4+ years of relevant experience in data engineering or a closely related field.

• Strong Python skills and experience with data analysis libraries (Pandas, NumPy, SciPy).

• Hands-on relational SQL database development experience.

• Unix/Linux experience.

• Bachelor’s degree in Computer Science, Statistics, Informatics, Information Systems, or another quantitative field.

Desirable skills/experience:

• Object-oriented languages: Java, C++, etc.

• AWS cloud services: EC2, RDS, Athena, Lambda, etc.

• RDBMS: SQL Server and PostgreSQL.

• Identity and Access Management: Kerberos, OAuth 2.0, LDAP.

• Other technologies: Apache HTTP Server, Kafka, Snowflake.

• Broad understanding of credit, fixed income, derivatives, futures, FX, or other financial instruments.

Other Qualifications:

• Excellent listening and communication skills (both oral and written).

• Self-starter and critical thinker; takes ownership of projects and suggests improvements to the broader infrastructure.

• Proactive, assertive, and attentive to detail.

• Able to work both independently and collaboratively.

• Comfortable handling multiple projects with competing priorities in a fast-paced environment.

• Strong self-management and problem-solving skills.

• Quick learner.