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Geopandas Python Jobs in Mountain View, CA (NOW HIRING)

Data Engineer (SE / Sr SE)

Santa Clara, CA · On-site

$122K - $168K/yr

You will work primarily in Python across large-scale data processing, geospatial analytics ... joins, PostGIS, GeoPandas, or map-based visualization libraries * Experience with release ...

You will work primarily in Python across large-scale data processing, geospatial analytics ... joins, PostGIS, GeoPandas, or map-based visualization libraries * Experience with release ...

You will work primarily in Python across large-scale data processing, geospatial analytics ... joins, PostGIS, GeoPandas, or map-based visualization libraries * Experience with release ...

Geopandas Python information

See Mountain View, CA salary details

$15

$69

$101

How much do geopandas python jobs pay per hour?

As of Aug 26, 2026, the average hourly pay for geopandas python in Mountain View, CA is $69.15, according to ZipRecruiter salary data. Most workers in this role earn between $57.02 and $78.56 per hour, depending on experience, location, and employer.

What is GeoPandas in Python?

GeoPandas is an open-source Python library that simplifies working with geospatial data. It extends the popular Pandas library to enable spatial operations on geometric types, such as points, lines, and polygons. With GeoPandas, users can easily read, write, and manipulate geographic data formats like Shapefile, GeoJSON, and others. It integrates well with other libraries, such as Matplotlib for visualization and Shapely for advanced geometric operations, making it a powerful tool for geographic data analysis in Python.

What are the key skills and qualifications needed to thrive as a Geopandas Python developer?

To thrive as a Geopandas Python Developer, you need a solid foundation in Python programming, geospatial data analysis, and GIS concepts, often backed by a degree in computer science or geography. Familiarity with Geopandas, Shapely, Fiona, and other geospatial libraries, as well as experience with spatial databases and data visualization tools, is typically required. Strong problem-solving skills, attention to detail, and effective communication help you deliver robust geospatial solutions and collaborate with team members. These skills are critical for accurately processing spatial data, generating valuable insights, and supporting data-driven decision-making in various industries.

What are some common challenges Geopandas Python developers face when working with large geospatial datasets?

Geopandas Python developers often encounter performance limitations when processing very large geospatial datasets, as Geopandas is built on top of Pandas and can be memory-intensive. Handling operations like spatial joins, dissolves, or aggregations on millions of features may lead to slowdowns or memory errors. To address these challenges, developers frequently use techniques such as chunking data, leveraging Dask for parallel computing, or integrating with more scalable libraries like PostGIS or PyGEOS. Collaborating closely with data engineers and GIS specialists can also help optimize workflows and ensure efficient data processing.

What is the difference between Geopandas Python vs GIS Analyst?

AspectGeopandas PythonGIS Analyst
Required CredentialsPython programming, GIS fundamentalsGIS certifications, degree in geography or related field
Work EnvironmentData analysis, scripting, codingMap creation, spatial data management, report generation
Industry UsageData science, software development, geospatial analysisUrban planning, environmental management, government agencies

Geopandas Python focuses on spatial data analysis using Python programming, ideal for data scientists and developers. GIS Analysts work with spatial data in various industries, often using GIS software and tools. While both roles involve geospatial data, Geopandas Python emphasizes coding and automation, whereas GIS Analysts focus on data management and visualization.

What job categories do people searching Geopandas Python jobs in Mountain View, CA look for?

The top searched job categories for Geopandas Python jobs in Mountain View, CA are:

What cities near Mountain View, CA are hiring for Geopandas Python jobs?

Cities near Mountain View, CA with the most Geopandas Python job openings:

Visiting Scientist (San Francisco Office)

NextGenEnergyJobs

San Francisco, CA • On-site

$85 - $120/hr

Other

Medical, Dental, Vision, PTO

Posted 8 days ago


Job description

Planet designs, builds, and operates the largest constellation of imaging satellites in history.

Key Responsibilities
  • We are seeking a highly motivated Visiting Scientist (Postdoctoral Researcher) to join our AI Research (AIR) team for a one-year residency. In this role, you will work directly with Dr. Mirela Tulbure during her sabbatical at Planet to develop our proprietary geospatial foundation models (GFMs).
  • While Planet has historically leveraged external models, we are now focused on building in-house models specifically trained on our unique imagery. As a postdoctoral researcher, you will be the primary technical engine behind creating temporally dense embeddings that capture the dynamic and ephemeral nature of our planet—such as rapid flooding and disaster impacts. You will collaborate with "Planeteers" across data pipelines and analytics to bridge the gap between academic research and operational AI/ML solutions.
Requirements
  • Academic Foundation: A recently completed PhD in Geospatial Analytics, Computer Science, Remote Sensing, or a related field.
  • Research Track Record: Demonstrated experience in building AI-based models for environmental change or satellite image analysis.
  • AI/ML Fluency: Hands-on experience with foundation models, contrastive learning, and deep learning frameworks (PyTorch/TensorFlow).
  • Advanced Technical Stack: Expert-level Python skills and proficiency with the geospatial scientific stack (e.g., xarray, Dask, Rasterio, GeoPandas).
  • Data Engineering Aptitude: Experience building automated pipelines for preprocessing and labeling planetary-scale datasets.
  • Collaborative Research: Experience working within a research lab environment and a strong desire to apply academic rigor to industry challenges.
  • Specialized Domain Knowledge: Prior research in flood-extent mapping, water dynamics, or disaster response.
  • GFM Fine-Tuning: Direct experience fine-tuning or modifying specific GFM architectures like TerraMind, Prithvi, or Clay.
  • Multi-Sensor Expertise: Proven ability to work with a variety of sensors including PlanetScope, Landsat, and Sentinel-1/2.
  • Operational Mindset: A history of developing "human-in-the-loop" workflows or active learning strategies for labeling time-sensitive data.
  • These offerings are dependent on employment type and geographical location, based upon applicable law or company policy.
  • Comprehensive Medical, Dental, and Vision plans
  • Health Savings Account (HSA) with a company contribution
  • Generous Paid Time Off in addition to holidays and company-wide days off
  • 16 Weeks of Paid Parental Leave
  • Wellness Program and Employee Assistance Program (EAP)
  • Home Office Reimbursement
  • Monthly Phone and Internet Reimbursement
  • Tuition Reimbursement and access to LinkedIn Learning
  • Equity
  • Commuter Benefits (if local to an office)
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