Data Analyst I Geospatial and Water Resources

Lynker Technologies; Boulder (CO); On-site; USD 60,000 - 75,000; Full time

Job summary

Lynker Technologies is seeking a Data Analyst I focused on geospatial and water resources in Boulder, CO. The role involves acquiring, cleaning, and integrating national geospatial datasets, writing robust data processing scripts in Python and SQL, and performing QA/QC on outputs.

You will coordinate with partner analysts and maintain metadata and releases for government clients. The candidate should have a quantitative Bachelor's degree and 0–2 years of related experience, with proficiency in

Qualifications

• Bachelor's degree in data science, statistics, computer science, geography, GIS, environmental science, hydrology, engineering, or related field.
• 0-2 years of professional or internship experience in data analysis, data engineering, or software development.
• Proficiency in Python for data work, including pandas.
• Proficiency with SQL and relational databases.
• Familiarity with Git and collaborative code review.
• Experience turning raw data into documented results through a technical task.

Responsibilities

• Acquire, clean, and integrate national-scale geospatial and hydrologic datasets.
• Write and maintain data processing scripts in Python and SQL with documentation.
• Run QA/QC checks on geospatial products and model outputs.
• Assemble validation datasets and produce accuracy summaries.
• Produce tables, figures, maps, and statistics for memoranda and reports.
• Maintain metadata, data dictionaries, and versioned releases.
• Work with cloud storage and formats (S3, GeoParquet, cloud-optimized GeoTIFF, Zarr).
• Coordinate with partner-organization analysts and developers on data standards and hand-offs.

Skills

Python

SQL

Git

Education

Bachelor's degree in a quantitative field

Tools

Pandas

Geospatial tools

Job description

Lynker Technologies

Data Analyst I Geospatial and Water Resources

US-CO-Boulder

Job ID: 2026-1662

Type: Full-Time

# of Openings: 1

Boulder - CO

Overview

Lynker Corporation is a leading provider of innovative solutions in weather and climate science. With a commitment to excellence and a passion for innovation, Lynker leverages cutting-edge technologies and scientific expertise to support the creation and delivery of improved operational weather forecasts.

Responsibilities

Duties of the Data Anaylst Iwill include the following:

• Acquire, clean, and integrate national-scale geospatial and hydrologic datasets, including surface water hydrography, wetlands inventories, soils, terrain, land cover, and gaged streamflow and precipitation records.
• Write and maintain repeatable data processing scripts in Python and SQL, under version control, with documented inputs, parameters, and outputs.
• Run QA/QC checks on derived geospatial products and model outputs; find spatial and attribute errors, quantify how widespread they are, and upscale what you can't resolve.
• Assemble validation and reference datasets from field-verified and independently mapped sources, and produce accuracy summaries (confusion matrices, error rates by class and by region) using methods defined by the technical lead.
• Produce the tables, figures, maps, and summary statistics that go into technical memoranda, monthly reports, and client review meetings.
• Maintain metadata, data dictionaries, and versioned data releases sufficient for a government client to reproduce results independently.
• Work with cloud storage and analysis-ready formats (S3, GeoParquet, cloud-optimized GeoTIFF, Zarr) to keep large datasets usable by the broader team.
• Coordinate day to day with partner-organization analysts and developers on shared data standards and hand-offs.

Qualifications

The Data Analyst I selected should have the following:

• Bachelor's degree in data science, statistics, computer science, geography, GIS, environmental science, hydrology, engineering, or a related quantitative field. A master's degree in a relevant field may substitute for experience.
• 0-2 years of professional or internship experience in data analysis, data engineering, or software development.
• Working proficiency in Python for data work, including pandas, plus the ability to pick up new libraries quickly.
• Proficiency with SQL and relational databases.
• Familiarity with Git and collaborative code review.
• Demonstrated experience carrying a technical task from raw data to a finished, documented result - coursework, capstone, internship, or