Senior Data Engineer
About The Position
The Space Telescope Science Institute (STScI), operated by the Association of Universities for Research in Astronomy (AURA), is NASA’s science operations center for missions including the Hubble and James Webb Space Telescopes. We are seeking a Senior Data Engineer to join our Data Management Division. We’re looking for a talented and experienced professional to help manage the backend data pipelines, MPP database system and ensure high-performance, reliable data access for our advanced astronomical public data archive, the Mikulski Archive for Space Telescopes (MAST)one of the world’s most advanced astronomical public data archives— serving missions such as HST, JWST, Roman, and TESS. This position can support hybrid work (around twice a quarter, in the office). Candidates must reside in or be willing to relocate to our local market. (MD, DE, VA, PA, DC & WV). This position requires US Citizenship or Permanent Residence to meet ITAR requirements. We’re hiring a Senior Data Engineer with strong core engineering skills and a passion for building robust, scalable data platforms. You’ll work hands-on with real scientific datasets, modern ETL/ELT data pipelines, and advanced distributed systems in a collaborative environment that supports rapid growth. Show us your GitHub, your projects, your passion. We highly value strong fundamentals and learning agility. If you’re a capable senior engineer ready to expand your expertise in modern data lake and query engine technologies, we’d love to hear from you.
Requirements
- Advanced expertise in PostgreSQL and Greenplum MPP
- Strong proficiency with Apache Airflow
- Hands-on experience with AWS cloud services
- Strong Python programming skills and proficiency in SQL and SQL performance tuning
- Strong experience designing, building, and optimizing data pipelines at scale
- Bachelor’s or master’s degree in computer science, Information Technology, or a related discipline
- 8+ years of experience as a data engineer with proven expertise in Python, PostgreSQL, Airflow, AWS services, and production-grade practices
Nice To Haves
- Specialized technologies such as Trino for distributed querying, Apache Iceberg for lakehouse management, Greenplum or other MPP systems, and large-scale performance tuning
- Tackling complex challenges with high-volume scientific data, query optimization, and modern data infrastructure
Responsibilities
- Design, develop, deploy, monitor, and troubleshoot complex data pipelines using Apache Airflow to process, transform, and load large-scale datasets efficiently and reliably.
- Build, maintain, and continuously improve data systems supporting scientific research, including relational databases and cloud-based Lakehouse.
- Ensure data accuracy, accessibility, observability, and reliability through proactive monitoring, alerting, and incident response.
- Work with scientists, data engineers, and cross-functional teams to translate requirements into robust, scalable platform solutions.
Benefits
- Employer retirement contribution – direct STScI contribution of 10% of your salary from your first day
- 12 days sick leave, up to 24 days’ vacation, and 10 paid holidays
- Flexible work schedule with healthy work/life balance
- Comprehensive medical/dental/vision/prescription plans, and more!
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What This Job Offers
Job Type
Full-time
Career Level
Senior
