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 Space Telescope and the James Webb Space Telescope.

We are seeking a hands‑on Senior Database Engineer with deep expertise in PostgreSQL to help design, build, and maintain performant databases. You will work as part of a team supporting reliable, high‑performance data flow for analytics, reporting, and science applications using Python and Apache Airflow. Some experience with AWS is required to efficiently support our growing data volumes.

This role will also involve working with others to optimize our Massively Parallel Processing (MPP) database system and help deliver fast, reliable data access for the Mikulski Archive for Space Telescopes (MAST) - one of the world’s most advanced public astronomical data archives.

This position supports hybrid work (approximately twice per quarter on site). Candidates must reside in or be willing to relocate to our local market (MD, DE, VA, PA, DC, or WV). U.S. Citizenship or Permanent Residence is required to meet ITAR requirements.

This is a technical individual contributor role, with opportunities to mentor junior database engineers and contribute to ongoing improvements of the data platform.

Key Responsibilities

• Act as the PostgreSQL subject matter expert: design efficient database schemas, optimize complex queries, implement advanced indexing strategies, and lead performance tuning, replication, partitioning, and high availability solutions
• Design, develop, optimize, and maintain data pipelines using Apache Airflow for orchestration and scheduling
• Work with AWS services to deploy and scale cloud‑based data infrastructure
• Participate in documentation, write clean and maintainable code, and engage in code reviews
• Mentor junior data engineers on best practices for PostgreSQL, Python, and Airflow

Required Qualifications

• Strong PostgreSQL experience, including schema design, partitioning, advanced SQL, query optimization, indexing, vacuuming, and EXPLAIN analysis
• Strong Python skills, with experience writing production‑grade scripts for data processing and automation; familiarity with libraries such as pandas, SQLAlchemy, and psycopg2
• Apache Airflow experience in production environments, including DAG development, scheduling, operators, sensors, and dependency management
• Bachelor’s or Master’s degree in Computer Science, Computer Engineering, Information Technology, or a related field
• 8+ years of professional experience in Linux‑based environments, with deep expertise in data engineering, data management, and scalable distributed data architectures

Our excellent benefits include: