Pacific States Marine Fisheries Commission (PSMFC) is recruiting candidates to fill the role of a mid-level Data Engineer / Database Specialist, working closely with USGS researchers at the Klamath Falls Field Station. The incumbent will support long-term research on endangered Lost River and Shortnose suckers, helping translate decades of biological, telemetry, and environmental data into insights that guide species recovery and water management in the Klamath Basin.
This role meaningful responsibility and real-world impact. The incumbent will design and build modern, cloud-enabled data systems, improve legacy workflows, and collaborate directly with scientists to advance critical research.
The position is based in Portland, Oregon and includes regular travel to Klamath Falls (approximately one week per month) to work on-site with the USGS researchers, with a potential option to relocate to Klamath Falls, Oregon.
Group Definition: Database Management Specialists develop and administer large-scale, multi-agency database systems. They have responsibility for maintenance, tuning, running backup and recovery, growing the system, administering permissions and security, and assuring continuous system availability.
Our Team
The incumbent will join a small, highly collaborative team working closely with USGS scientists to turn research needs into technical solutions. The incumbent will perform query and analyze data, support modeling and system performance, and help modernize workflows. In this role, the incumbent will also collaborate with IT on security and access, contribute to data governance practices, and support GIS and field data collection systems, while helping teammates grow through knowledge sharing and collaboration.
Project Specifics
Contribute to the design and modernization data systems that support fisheries research and real-world decision making in the Klamath Basin. Build reliable, scalable data platforms, improve legacy systems, and collaborate closely with scientists to turn complex data into actionable insights. We don't expect candidates to bring experience in every listed technology—strength in core data skills and a willingness to learn are what matter most.
Essential Functions
The data professional should have 3+ years of experience and can design, build, and improve scientific data systems. The ideal candidate brings strong data engineering and database skills, along with the ability to collaborate effectively with scientists and IT partners.
Data & Platform Management
- Design, build, and maintain relational databases (e.g., SQL Server, SQLite)
- Perform data modeling, schema design, and performance optimization
- Implement reliability practices (backup/recovery, access controls, availability)
- Maintain documentation and support data stewardship practices
- Troubleshoot and resolve database performance and integrity issues
Data Engineering & Integration
- 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
Analytics & Data Products
- Develop queries and reporting solutions (e.g., Power BI)
- Build reproducible analytical workflows in Python or R
Collaboration
- Partner with scientists, engineers, and IT staff
- Communicate technical concepts to non-technical audiences
Support Modernization
- Support migration of legacy systems into modern, cloud-enabled environments
- Contribute to ongoing system and workflow improvements
Additional Mandatory Skills:
Databases and Data Engineering
- 3+ years of experience in data engineering and/or database administration
Programming languages:
- Strong SQL proficiency and at least one scripting language (Python or R)
Additional Desirable Skills:
Data & Data Architecture
- Experience with data architecture and system design
Cloud and Modern Platforms
- Knowledge of cloud platforms (Azure preferred; AWS/GCP acceptable)
- Familiarity with workflow automation or orchestration tools
Analytics & Visualization
- Knowledge of dashboards, Power BI or similar data visualization tools
- Familiarity AI assisted tools
GIS Technology and Field Data Systems
- Exposure to GIS systems (ArcGIS, QGIS) or spatial data is a plus
- Support ingestion workflows for field/mobile data collection systems (e.g., data from ESRI Survey123).
Data Governance & Lifecycle Management
- Contribute to improving data governance or metadata practices
- Familiarity with data lifecycle management and long-term data stewardship concepts
Operating Systems and Legacy Support
- Support migrating legacy systems or applications (C#, VB)
- Familiarity with Windows Server and/or Linux environments
Domain Experience
- Familiarity working with scientific, environmental, or ecological datasets
- Familiarity with fisheries data, telemetry, tagging, or movement data
Collaboration and Leadership Skills
- Interact with contractors and with IT on security, permissions, and cloud migration (e.g., Azure)
- Help team members grow by sharing knowledge and providing guidance
Knowledge Required by the Position:
- Database management concepts, principles, and methods including database logical and physical design, normalization, storage capacity management, and back-up and recovery.
- Data flow design and business process design.
- Sources, characteristics, and uses of the organization's data assets.
- Database management systems, query languages, table relationships, and views.
- Data mining and data warehousing principles
- The characteristics of physical and virtual data storage media.
- Data administration and data standardization policies and standards in developing and managing large-scale, multi-agency databases.
Physical Demands:
The work is sedentary with moderate walking between workstations and carrying folders, reports, and similar light loads.
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.
Requirements:
Minimum Qualification Requirements:
Candidates must present one year of Specialized Experience which demonstrates:
- Knowledge of customary approaches, techniques, and requirements appropriate to database management;
- Knowledge of planning sequences necessary to accomplish assignments where this entailed coordination with others outside the organizational unit and development of project controls; and
- Adaptation of guidelines or precedents to the needs of the assignment.
The Specialized Experience must equip the candidate with the particular knowledge, skills, and abilities to perform successfully the duties of the position and is typically in or related to the work of the position to be filled. To be creditable, the Specialized Experience must have been equivalent to at least the next lower level in the normal line of progression position.
To work with USGS Data Systems, the Candidate must also meet the below minimum requirements:
- Federal System Access: Must meet federal eligibility requirements to access and utilize federal data systems.
- Citizenship & Residency: Due to federal security mandates, this position requires U.S. citizenship or lawful permanent residency (Green Card holder) maintained for a minimum of three consecutive years.
- Background Investigation: Position is contingent upon the successful completion of a comprehensive federal agency background investigation.
- Driving Clearance: Offers of employment for positions located in Oregon are contingent upon supplying and clearing an MVR check. The selected candidate must provide PSMFC with a copy of their 3-Year Oregon Motor Vehicle Record (MVR) and are are responsible for all associated DMV fees.
Required Application Materials
Requirement A - Resume
Resume (max 3 pages) that clearly demonstrates relevant experience with databases, data engineering, or analytics
Technical skills aligned with the Essential Functions and Additional Mandatory Skills.
Requirement B - Supplemental Technical Responses
In lieu of a traditional cover letter, provide concise responses to the questions below. Brief focused examples and outcomes are sufficient.
- Describe your experience working with relational databases (e.g., SQL Server, SQLite), including any work with performance optimization, reliability, or system maintenance. Include work samples as applicable within the document, shared via links (GitHub, portfolio, etc.) or uploaded as separate documents.
- Share an example of how you have built or worked with data pipelines or automated workflows (ETL/ELT, scripting, or similar tools). Include work samples as applicable within the document, shared via links (GitHub, portfolio, etc.) or uploaded as separate documents.
- Provide an example of how you improved, migrated, or modernized an existing data system, process, or workflow.
- Describe a project where you collaborated with non-technical partners (e.g., scientists, analysts, program staff). How did you translate needs into a data or technical solution?
- Highlight any experience with cloud platforms, GIS/spatial data, or scientific / environmental datasets (if applicable).
