Data Engineer

The Center for Guaranteed Income Research (CGIR) is an unconditional cash-transfer research center headquartered at the School of Social Policy & Practice at the University of Pennsylvania. CGIR conducts applied cash-transfer studies and pilot designs in concert with community-based organizations and government stakeholders to add to the empirical scholarship on cash, economic mobility, and poverty. CGIR is currently conducting the world’s largest multi-site evaluation of nearly 40 guaranteed income pilots across the nation as part of The American Guaranteed Income Studies (AmGIS). Using a common research design and a core survey across its pilot sites, the aims of AmGIS are to (1) facilitate comparisons across pilot sites, and (2) create a singular master dataset pooling data from more than 19,000 study participants across treatment and control groups. In addition, CGIR is augmenting its original survey data with administrative data from across its diverse pilot sites.

The Data Engineer will work closely with CGIR’s Biostatistician, Center Leadership, and Research Scientists to design and manage the data infrastructure for the AmGIS sites described above. This portfolio of work includes: (1) the organization and structuring of raw data; (2) the oversight of data quality assurance, cleaning, and control activities; (3) the collation of individual site-specific datasets into a singular, master dataset; (4) the integration of original, survey data with administrative data; and (5) the security, integrity, and storage of data sets, codebooks, coding, and other associated documentation. In sum, the Data Engineer will be responsible for all tasks related to data acquisition; data transformation and cleaning; data integration; and data storage and security. In addition, the Data Engineer will also supervise student research assistants.

A bachelor’s degree and 3 -5 years’ experience is required. Preferably in computer engineering, information systems or a related field is required, and an advanced graduate degree is preferred. A minimum of 1-2 years of professional experience in data engineering, cloud platforms or database is mandatory with demonstrated expertise in coding and programming in both SQL and Python, data warehousing, machine learning, cloud computing, data integration tools, and data security. Additional requisite skills include strong critical thinking, interpersonal, communication, problem-solving skills, and experience supervising. This is a hybrid position with a requirement of 2-3 days per week in-person on campus. We expect this position to fill quickly. Prospective candidates are encouraged to apply as early as possible.