Data Engineer I: HR Data Pipelines & Analytics

The Johns Hopkins University; Baltimore (MD); Hybrid; USD 88,000 - 154,000; Full time

Job summary

The Johns Hopkins University seeks a Data Engineer I to design and maintain data pipelines, enabling acquisition, transformation, and delivery of data for visualization and decision support. You will work on ETL/ELT processes, data quality monitoring, and scripts for data cleaning and preparation, collaborating with researchers, policy experts, and developers across the organization.

This hybrid role at Johns Hopkins University emphasizes enterprise data architectures, HR analytics, and scalable

Qualifications

• Bachelor’s degree required with related experience.
• Three years of relevant experience or equivalent education substituted per policy.
• Experience with ETL/ELT and data warehousing concepts.

Responsibilities

• Design, develop, and maintain data pipelines for acquisition, management, and transformation.
• Develop and maintain ETL/ELTs across sources, structured and unstructured.
• Support data scraping systems and data architecture, ensuring data quality.
• Input/output data from databases and perform queries to aid analyses.
• Create scripts to clean, transform, and analyze data for visualization.

Skills

Data pipeline

ETL/ELT development

Database querying

Data warehousing

Data validation

Web scraping

Programming languages

Troubleshooting

Project management

Education

Bachelor’s Degree

Tools

Workday HCM

SAP HCM

HR data warehouse

Power BI

Tableau

Workday Reporting

Prism Analytics

Job description

The Johns Hopkins University seeks a Data Engineer I to design and maintain data pipelines, enabling acquisition, transformation, and delivery of data for visualization and decision support. You will work on ETL/ELT processes, data quality monitoring, and scripts for data cleaning and preparation, collaborating with researchers, policy experts, and developers across the organization.

This hybrid role at Johns Hopkins University emphasizes enterprise data architectures, HR analytics, and scalable