Data Engineer I: Public Health Data & Modeling

John Hopkin’s University; Baltimore (MD); Presencial; USD 88.000 - 154.000; Jornada completa

Descripción de la vacante

Johns Hopkins University in the School of Public Health seeks a Data Engineer I to design, build, and maintain complex data pipelines, from raw data acquisition to visualization, powering research dashboards and web applications.

The role includes developing ETL processes, ensuring data quality, and writing scripts for data cleaning and transformation to support policy-relevant analyses.

Formación

• Bachelor’s degree required.
• Three years of related experience required.
• Additional education or experience may substitute for required education/experience as permitted.

Responsabilidades

• Assist with design, production, and maintenance of data pipelines for acquisition, management, and transformation.
• Contribute to ETL/ELT development across structured and unstructured sources.
• Support web data scraping systems for automatic data acquisition.
• Assist data architecture design and ongoing support.
• Handle input/output data from databases and perform queries.
• Create scripts to clean, transform, and analyze data.
• Contribute to production data pipelines using data warehousing systems.
• Create production software to monitor data quality and detect anomalies.
• Perform daily data quality assurance tasks.
• Support, maintain, and troubleshoot the software infrastructure.
• Source data, conduct analyses, visualize data, and generate insights for research.
• Collaborate with developers, analysts, data scientists, researchers, policy experts, and partners.

Conocimientos

Data Pipeline Architecture

ETL/ELT Development

Database Querying

Data Tools and Platforms

Data Validation and QA

Data Warehousing

Project Management

Programming Languages

Troubleshooting

Web Scraping and Data Acquisition

Educación

Bachelor’s Degree

Descripción del empleo

Johns Hopkins University in the School of Public Health seeks a Data Engineer I to design, build, and maintain complex data pipelines, from raw data acquisition to visualization, powering research dashboards and web applications.

The role includes developing ETL processes, ensuring data quality, and writing scripts for data cleaning and transformation to support policy-relevant analyses.