Data Engineer

Overview

The Department of Sociology at Princeton University seeks applicants for a full-time Data Engineer position in the Eviction Lab. Successful candidates will have a background in data science and/or computer science. The data engineer will contribute to the Eviction Lab at Princeton University’s mission to create data and research products to help researchers, policymakers, and community members understand the eviction crisis.

 

Salary is competitive and is benefits-eligible. Applicants should submit a dossier including: (1) a complete vita, (2) a cover letter of interest, (3) names and contact information of up to three persons who can serve as references, (4) a coding sample or data product that speaks to applicant’s experience with relevant tasks. All materials should be submitted as 1 continuous PDF. Applications will be considered on a rolling basis. Start date is flexible. Materials submitted by regular mail or email will not be accepted.

 

The responsibilities of the position are to lead the development of a data construction pipeline for processing large-scale administrative records. This would involve writing code to create new data products (e.g., geocoding addresses, cleaning names, combining multiple sources of data) in a reproducible way; writing tests to assess the quality of the data products created by the pipeline; writing tests to assess the speed of the pipeline; optimizing the code to improve quality and speed; cleaning and reformatting incoming datasets to conform to the pipeline; running the pipeline using these datasets; and identifying and fixing bugs, among other tasks. The datasets used are very large and require the use of remote computing clusters. Applicants with experience using very large datasets and optimizing code to run efficiently are preferred.

 

This is a one-year term position with the possibility of renewal. You would work directly with a project lead, but much of the work would be carried out independently. The ideal candidate is someone who is self-motivated and can identify the larger goals of the project and propose relevant, useful tasks in a self-directed way.

Responsibilities

Job duties include:

• Improving existing code base: reviewing code base; designing tests to assess data quality; designing tests to assess speed and identify bottlenecks; rewriting code to optimize speed and quality and remove extraneous operations.
• Developing a data pipeline for new datasets: preprocessing data to conform to uniform data standards; identifying missing data and making appropriate imputations; running standardized data through data construction pipeline; identifying and fixing bugs; assessing resulting data products for accuracy and completeness.
• Leading the development of new data features and products: constructing new measures and assessing them for accuracy; incorporating new types of data and making measures based on them.

Qualifications

Essential Qualifications:

• Bachelor's degree or equivalent
• 3+ years of relevant experience
• Extensive experience writing data pipelines written in python, specifically Pandas and GeoPandas
• Extensive experience working with large datasets
• Familiarity with mapping and geographic data processing
• Familiarity with Git
• Demonstrated ability to work independently
• Knowledge of regular expressions (regex)

Preferred Qualifications:

• Database management tools (e.g., SQL)
• R
• ArcGIS or other GIS software
• Experience using administrative data

Princeton University is an Equal Opportunity and all qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity or expression, national origin, disability status, protected veteran status, or any other characteristic protected by law. KNOW YOUR RIGHTS

Standard Weekly Hours

36.25

Eligible for Overtime

No

Benefits Eligible

Yes

Probationary Period

180 days

Essential Services Personnel (see policy for detail)

No

Estimated Appointment End Date

6/2/2026

Physical Capacity Exam Required

No

Valid Driver’s License Required

No

Experience Level

Mid-Senior Level

#LI-JJ1