Part-Time Data Engineer

This is a part-time, temporary, remote position. The expected start date is May 8, and the expected end date is December 31, with 10 hours of weekly work expected.

The Data Engineer supports the GO Foundation in developing, implementing, managing, and supporting student and staff data and information systems. They ensure that our data infrastructure can meet the demands of a rapidly growing organization. This work is critical for ensuring progress towards impact goals and overall quality of the GO Foundation and its AmeriCorps Fellowship program.

The Data Engineer focuses on data analytics and engineering, visualization, and governance. Specific responsibilities include:

• Managing recruitment dashboard updates
• Managing school dashboard updates
• Tracking daily data pulls and troubleshooting as issues arise
• Tracking report usage
• Supporting other workflows as assigned such as surveys, student data collection, state-specific data requirements, Fellow observation tools, and data validation
  
  

The Data Engineer reports directly to Director of Data and Research.

Compensation & Benefits

• $50/hourly rate
• An invoice showing the hours worked will be required for payment. Once received, payment will be made within 5-7 business days via bill.com.
• No additional benefits are provided
  
  

Qualifications

The following skills are required for the position:

• Coding: Experience with at least one of the following coding languages: SQL, Python, R
• Data visualization: Experience with visualization software, such as: Looker Studio, Tableau, Power BI
• Engineering: Experience with at least one of the following techniques: Data validation, Data treatment (extract, transform, load), Star Schema data model, Data orchestration
  
  

The additional skills listed below are not required but could help drive success this role:

• Qualitative and Quantitative Research Methods: Experience with interviewing and thematic coding, and/or a background in statistical analysis
• Survey Development and Analysis: Experience with development, administration, and analysis
• Cloud software: Knowledge of Cloud software (Google Cloud, BigQuery), ETL software (Dataform, DBT), Data pipeline automation (FiveTran), and/or Data orchestration (Datalore or Dagster)