Geospatial Data Specialist — 2D/3D Mapping & QA

Blood Hound Underground Utility Locators

Zionsville (IN)

Hybrid

USD 28,000 - 41,000

Full time

7 days ago
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Job summary

Blood Hound Underground Utility Locators is seeking a detail‑oriented Geospatial Data Processing Specialist to transform sensor data (GPR, LiDAR, GNSS, UAS imagery) into precise deliverables for engineering and construction decisions.

You’ll collaborate with the Geospatial Systems Supervisor, CAD and GIS teams and field crews to ensure high accuracy from field to deliverable, with a focus on data quality and reproducibility across platforms.

Qualifications

  • 1+ years of geospatial data processing or GIS/CAD production experience.
  • Familiarity with LiDAR, GPR data formats and workflows preferred.
  • Bachelor’s degree or equivalent experience in geography/geomatics/engineering tech.

Responsibilities

  • Process geospatial datasets from LiDAR, GPR, GNSS and photogrammetry.
  • Perform QA/QC checks for alignment and completeness.
  • Convert and clean datasets for CAD, GIS, BIM imports (Civil 3D, QGIS, Revit).
  • Generate 2D/3D outputs (shapefiles, DWGs, KMLs, surfaces).
  • Standardize naming, coordinates and metadata across deliverables.
  • Collaborate to improve data pipelines and automation.
  • Maintain libraries, templates and processing docs.
  • Ensure data is archived per company protocols.
  • Communicate with field teams to resolve data issues.
  • Provide feedback to improve data capture quality.

Skills

Geospatial processing
Remote sensing
GIS/CAD production
QA/QC

Education

Bachelor degree in Geography or Geomatics

Tools

AutoCAD Civil 3D
QGIS

Job description

Blood Hound Underground Utility Locators is seeking a detail‑oriented Geospatial Data Processing Specialist to transform sensor data (GPR, LiDAR, GNSS, UAS imagery) into precise deliverables for engineering and construction decisions.

You’ll collaborate with the Geospatial Systems Supervisor, CAD and GIS teams and field crews to ensure high accuracy from field to deliverable, with a focus on data quality and reproducibility across platforms.

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