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 Catalog Science Branch. 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. 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 in order to meet ITAR requirements.

What You will Do:

• Architect and evolve end‑to‑end scientific data solutions
• Lead the design, development, and optimization of scalable relational databases and cloud-based data Lakehouse
• Develop, maintain and optimize robust, fault-tolerant data pipelines using Apache Airflow (or similar tools) for data ingestion and data migration to process petabyte-scale datasets efficiently
• Deploy and manage, scale containerized data workloads using Kubernetes on prem and in cloud
• Develop and maintain CI/CD pipelines for reliable automated deployment
• Partner with scientific, engineering, and non‑technical stakeholders to ensure data performance, accessibility, and reliability
• Serve as a senior technical contributor, providing guidance on best practices for data engineering

Required Technical Skills:

• Deep expertise in PostgreSQL: schema design, query optimization, indexing, partitioning, and large-scale performance tuning
• Strong experience designing and developing scalable data pipelines and modern cloud‑based data Lakehouse architectures
• Proficiency in Apache Airflow for developing, scheduling, monitoring, and troubleshooting data pipelines
• Hands-on experience with Kubernetes for container orchestration, including deploying and scaling workloads.
• Strong programming skills in Python (required) and shell scripting
• Excellent problem-solving abilities and be able to communicate technical concepts clearly to non-technical teams

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Information Technology, or a related field.
• 8+ years of professional experience in Linux-based environments, with demonstrated expertise in data engineering, data management, and scalable data architectures.