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Geospatial Data Engineer Remote Jobs in Antioch, CA

Tunabear

Data Engineer - AWS/Oracle

Oakland, CA · Remote

$117K - $140K/yr

Remote, CA hours (8am-5pm PST availability) Contract length: 6 months + likely extension Data Engineer Contractor - AWS / Oracle Position Overview We are seeking a hands-on Data Engineer Contractor ...

Match Point Solutions

Data Scientist

Pleasanton, CA · Remote

$75 - $80/hr

Remote Rate: $75-$80/hr on W2 Key points: Developing computer vision models that improve, accelerate, and automate asset inspections processes Strong Python programing Department Overview The Data ...

Data Piper

Databricks Architect

Pleasanton, CA · Remote

$72 - $94.50/hr

Remote 10+ years experience in data eng, data platforms & analytics, 10+ years of consulting experience Completed Data Engineering Professional certification & required classes Hands-on experience in ...

Data Piper

Databricks Architect

Pleasanton, CA · On-site +1

$72 - $94.50/hr

Remote • 10+ years experience in data eng, data platforms & analytics, 10+ years of consulting experience • Completed Data Engineering Professional certification & required classes • Hands-on ...

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All JobsGeospatial Data Engineer JobsGeospatial Data Engineer Remote JobsGeospatial Data Engineer Remote Jobs in Antioch, CA

Geospatial Data Engineer Remote information

See Antioch, CA salary details

$50.6K

$147.5K

$201.8K

How much do geospatial data engineer remote jobs pay per year?

As of Sep 12, 2026, the average yearly pay for geospatial data engineer remote in Antioch, CA is $147,484.00, according to ZipRecruiter salary data. Most workers in this role earn between $130,200.00 and $156,300.00 per year, depending on experience, location, and employer.

What is a geospatial data engineer?

A Geospatial Data Engineer is a technology professional who designs, develops, and manages systems for collecting, storing, analyzing, and visualizing geospatial (location-based) data. They work with geographic information systems (GIS), spatial databases, and cloud platforms to process large datasets from sources like satellites, drones, and sensors. In a remote setting, they collaborate with teams online to build and maintain geospatial data pipelines and support decision-making for industries such as urban planning, environmental science, and logistics.

What are the typical challenges faced by remote geospatial data engineers when collaborating with distributed teams?

Remote Geospatial Data Engineers often navigate challenges such as coordinating across different time zones, ensuring data consistency, and maintaining effective communication with team members who may have varying technical backgrounds. Utilizing collaborative tools like version control systems and cloud-based platforms helps streamline workflows, but clear documentation and regular check-ins are essential to prevent misunderstandings. Building strong relationships virtually and proactively addressing technical or logistical issues can greatly enhance productivity and teamwork in a remote setting.

What are the key skills and qualifications needed to thrive as a geospatial data engineer in a remote role, and why are they important?

To thrive as a Geospatial Data Engineer (Remote), you need a strong background in GIS, geospatial analysis, and computer science, often supported by a related degree and experience with spatial databases. Proficiency with tools like Python, SQL, PostGIS, ArcGIS, and cloud platforms is typically required, along with relevant certifications such as GISP. Excellent problem-solving, communication, and self-management skills are essential for collaborating across distributed teams and delivering results independently. These skills ensure effective management of complex geospatial datasets, seamless integration of spatial data solutions, and success in a remote work environment.

What is the difference between Geospatial Data Engineer Remote vs GIS Analyst?

AspectGeospatial Data Engineer RemoteGIS Analyst
Required CredentialsBachelor's in GIS, Geography, Computer Science; experience with GIS software and programmingBachelor's in Geography, GIS, or related field; proficiency in GIS tools
Work EnvironmentRemote, often collaborative with teams across locationsTypically office-based or hybrid; fieldwork possible
Employer & Industry UsageTech companies, government agencies, environmental firmsUrban planning, government, environmental consulting
Common Search & ComparisonOften compared for GIS and data engineering roles in remote settings

The main difference between a Geospatial Data Engineer Remote and a GIS Analyst lies in their focus and skill set. Geospatial Data Engineers primarily develop and maintain data pipelines and infrastructure, often requiring programming skills, while GIS Analysts focus on spatial data analysis and map creation. Both roles may work remotely and share similar educational backgrounds, but their daily tasks and technical expertise differ significantly.

What job categories do people searching Geospatial Data Engineer Remote jobs in Antioch, CA look for?

The top searched job categories for Geospatial Data Engineer Remote jobs in Antioch, CA are:

What cities near Antioch, CA are hiring for Geospatial Data Engineer Remote jobs?

Cities near Antioch, CA with the most Geospatial Data Engineer Remote job openings:

Geospatial Data Engineer Remote jobs near you
Infographic showing various Geospatial Data Engineer Remote job openings in Antioch, CA as of June 2026, with employment types broken down into 32% Full Time, and 68% Part Time. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $147,484 per year, or $70.9 per hour.

Data Engineer - AWS/Oracle

Oakland, CA • Remote

Tunabear
IT Services • 51 - 200 employees
Learn more about Tunabearexternal

$117K - $140K/yr

Contractor

Posted 8 days ago

Job description

Contract role:  1099, C2C
Location:  Remote, CA hours (8am-5pm PST availability)
Contract length:  6 months + likely extension
 

Data Engineer Contractor – AWS / Oracle
Position Overview

We are seeking a hands-on Data Engineer Contractor to support our Reporting Instance (RI) and Self-Managed Hosting (SMH) project initiatives. The engineer will be responsible for developing and supporting scalable data pipelines, ETL processes, data validation, batch processing, and AWS-based data solutions. The ideal candidate has strong experience with AWS Glue, AWS Lambda, Oracle SQL/PL/SQL, and troubleshooting complex data environments.

Key Responsibilities
  • Design, develop, and support ETL/ELT data pipelines using AWS Glue.
  • Develop and maintain AWS Lambda functions for data processing, automation, and event-driven workflows.
  • Build and support data flows for downstream reporting and analytics systems.
  • Work with Oracle SQL and PL/SQL to develop, troubleshoot, and optimize data processing workloads.
  • Validate end-to-end data flows and ensure data quality, integrity, and consistency.
  • Monitor and troubleshoot batch jobs, pipeline failures, data issues, and operational problems.
  • Support AWS environment configuration, deployment, and operational readiness in collaboration with Infrastructure teams.
  • Perform SQL and pipeline performance tuning, including query optimization, execution-plan analysis, indexing, materialized views, partitioning, and parallel processing where appropriate.
  • Optimize ETL processes, batch jobs, and data refresh cycles for reliability and scalability.
  • Create technical documentation and participate in knowledge transfer.
Required Qualifications
  • Hands-on experience with AWS Glue and AWS Lambda.
  • Strong experience developing and supporting data pipelines and ETL processes.
  • Strong Oracle SQL and PL/SQL experience.
  • Experience working with large-scale or high-volume data environments.
  • Experience with data validation, troubleshooting, and batch processing.
  • Understanding of AWS cloud services and data integration patterns.
  • Strong problem-solving and communication skills.
  • Ability to work independently in a fast-paced operational environment.
Preferred Qualifications
  • Experience with Oracle performance tuning and execution-plan analysis.
  • Experience with materialized views, indexing, partitioning, and parallel processing.
  • Familiarity with batch scheduling and orchestration tools.
  • Experience working with Infrastructure and cross-functional teams.