Senior Data Engineer

Responsibilities

• Airflow Pipelines — 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.

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.

Qualifications

• 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.

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!

Pay

Salary range is $125,000 - $150,000. Final compensation is based on experience, skills, internal equity, and market conditions.

Schedule

This position can support hybrid work (around twice a quarter, in the office).