Join a small, highly collaborative team at the Pacific States Marine Fisheries Commission in Portland, OR, onsite. In this role, you’ll work with USGS researchers at the Klamath Falls Field Station to design and modernize data systems that translate diverse biological, telemetry, and environmental data into actionable insights for endangered Lost River and Shortnose suckers and for water management in the Klamath Basin.
Responsibilities
- Design, build, and improve scientific data architectures and systems.
- Collaborate effectively with scientists and IT partners.
- Design, build, and maintain relational databases such as SQL Server and SQLite.
- Perform data modeling, schema design, and optimize performance.
- Implement reliability practices including backup, recovery, access controls, and availability.
- Maintain documentation and support data stewardship practices.
- Troubleshoot and resolve database performance and integrity issues.
- Build and support automated data pipelines (ETL/ELT).
- Use SQL and scripting tools (Python, R, or similar) for data processing.
- Integrate diverse datasets into centralized systems.
- Refactor legacy scripts and workflows into scalable, automated pipelines.
- Develop queries and reporting solutions, including Power BI.
- Build reproducible analytical workflows in Python or R.
- Partner with scientists, engineers, and IT staff.
- Communicate technical concepts to non-technical audiences.
- Support migration of legacy systems into modern, cloud-enabled environments.
- Contribute to ongoing system and workflow improvements.
Requirements
Mandatory qualifications
- 3+ years of experience in data engineering and/or database administration.
- Strong SQL proficiency and at least one scripting language (Python or R).
Desirable qualifications
- Experience with data architecture and system design.
- Knowledge of cloud platforms (Azure preferred; AWS or GCP acceptable).
- Familiarity with workflow automation or orchestration tools.
- Knowledge of dashboards and data visualization tools such as Power BI.
- Familiarity with AI assisted tools.
- Exposure to GIS systems (ArcGIS, QGIS) or spatial data.
- Support ingestion workflows for field or mobile data collection systems (eg ESRI Survey123).
- Contribute to improving data governance or metadata practices.
- Familiarity with data lifecycle management and long-term data stewardship concepts.
- Support migrating legacy systems or applications (C#, VB).
- Familiarity with Windows Server and/or Linux environments.
- Experience with scientific, environmental, or ecological datasets.
- Familiarity with fisheries data, telemetry, tagging, or movement data.
- Coordinate with contractors and IT on security, permissions, and cloud migration (e.g., Azure).
- Help teammates grow by sharing knowledge and providing guidance.
Technologies used
- SQL Server
- SQLite
- Python
- R
- Power BI
- Azure
- AWS
- GCP
- ArcGIS
- QGIS
- ESRI Survey123
- Windows Server
- Linux
- C#
- VB
About the team
You will join a small, highly collaborative group that works closely with USGS scientists to translate research needs into technical solutions. The role includes querying and analyzing data, supporting modeling and system performance, and helping modernize workflows. Collaboration with IT on security and access, contribution to data governance, and support for GIS and field data collection systems are part of the role, with an emphasis on knowledge sharing to help teammates grow.
Project focus
Contribute to designing and modernizing data systems that support fisheries research and real world decision making in the Klamath Basin. Build reliable, scalable data platforms, improve legacy systems, and work closely with scientists to turn complex data into actionable insights. The focus is on strong core data skills and a willingness to learn, rather than proficiency in every listed technology.
Work environment
The work is performed in an office setting with adequate lighting, heating, and ventilation. There are the normal risks of an office environment.
Physical demands
The role is sedentary, with occasional light movement between workstations and carrying of folders or reports.
