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Geospatial Data Engineer Remote Jobs in Virginia

Anika Systems

Data Engineer

Leesburg, VA · On-site +1

$115K - $139K/yr

Anika Systems is seeking a skilled Data Engineer to design, build, and optimize scalable data ... This opportunity is 100% remote. The ideal candidate has hands-on experience with ETL/ELT pipelines ...

TEKsystems

Data Engineer

Richmond, VA · Remote

$60 - $80/hr

Description Seeking a Data/AI Engineer to build and scale automated data pipelines across a diverse ... remote position. Application Deadline This position is anticipated to close on Jul 10, 2026. About ...

GRVTY

Palantir Data Engineer

Chantilly, VA · On-site +1

$117K - $140K/yr

... support remote work) and requires a TS/SCI + Polygraph clearance (acceptable to this customer ... The Palantir Data Engineer leverages advanced Python skills within a small team to develop and ...

Shift5

Data Engineer

Arlington, VA · Remote

$130K - $170K/yr

We are seeking a Data Engineer to join our growing Product Engineering team. In this role, your ... Flexible work & remote work policy * Tax-deferred public transit benefits with Metro SmartBenefits ...

SAIC

AI Data Engineer

Fort Belvoir, VA · On-site +1

$160K - $200K/yr

TS/SCI with Poly Potential for Remote Work: ORA_ON_SITE Description SAIC is seeking an AI Data Engineer to join our team at Fort Belvoir, Virginia. The AI Data Engineer will design, develop, and ...

Edgesource

Data Engineer

Centreville, VA · On-site +1

$113K - $136K/yr

Client is seeking a data engineer to grow our team performing cutting edge client work in mission ... Schedules (Remote / Hybrid) - - Medical / Dental / Vision / Flexible Spending Account (FSA ...

Shift5

$130K - $170K/yr

We are seeking a Data Engineer to join our growing Product Engineering team. In this role, your ... Flexible work & remote work policy * Tax-deferred public transit benefits with Metro SmartBenefits ...

VTG

Software Engineer

Chantilly, VA · Remote

Bachelor's degree in Geospatial Intelligence, Geography, Remote Sensing, Intelligence Studies ... Experience in data modeling, partition sharding, stream processing, and metrics gathering.

GRVTY

Data & Software Engineer

Mclean, VA · On-site +1

$115K - $139K/yr

... support remote work) and requires a TS/SCI + Polygraph clearance (acceptable to this customer ... Geospatial. * Using Bash scripting for automation and data processing tasks * Integrating Al/ML ...

ICF

Data Engineer (Databricks)

Reston, VA · Remote

$119K - $143K/yr

This position is fully remote with up to 10% travel to the DC Metropolitan area for client meetings ... Databricks on Azure for data engineering and ML pipeline support. * SQL, Python, Spark, Tableau.

New

GRVTY

Full Stack Developer

Mclean, VA · On-site +1

$150K - $250K/yr

... Data Analysts, AWS Engineers, DevOps Engineers, Cloud Migration Experts, and Geospatial Systems Engineers. Work on this program takes place in the McLean, VA area (we cannot support remote work) and ...

Team Velocity

Senior Data Engineer

Herndon, VA · On-site +1

$150K - $195K/yr

We are seeking a Senior Data Engineer to design, develop, and scale the data platform that powers ... Experience working in a remote-first environment. COMPENSATION Compensation commensurate on ...

Team Velocity

Senior Data Engineer

Herndon, VA · Remote

$150K - $195K/yr

We are seeking a Senior Data Engineer to design, develop, and scale the data platform that powers ... Experience working in a remote-first environment. COMPENSATION Compensation commensurate on ...

Atreides

Mission (Data) Engineer

Arlington, VA · Remote

$131K - $158K/yr

Mission (Data)Engineer Travel: Approximately 10% international travel required. Number of Openings ... Flexible remote work environment * Additional benefits like flexible hours, work travel ...

Shift5

$185K - $220K/yr

We are seeking a Staff Data Engineer to join our growing Product Engineering team. In this role ... Flexible work & remote work policy * Tax-deferred public transit benefits with Metro SmartBenefits ...

Shift5

Staff Data Engineer

Arlington, VA · Remote

$185K - $220K/yr

We are seeking a Staff Data Engineer to join our growing Product Engineering team. In this role ... Flexible work & remote work policy  * Tax-deferred public transit benefits with Metro ...

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All JobsGeospatial Data Engineer JobsGeospatial Data Engineer Remote JobsGeospatial Data Engineer Remote Jobs in Virginia

Geospatial Data Engineer Remote information

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 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 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 most commonly searched types of Geospatial Data Engineer jobs in Virginia? The most popular types of Geospatial Data Engineer jobs in Virginia are:
What are popular job titles related to Geospatial Data Engineer Remote jobs in Virginia? For Geospatial Data Engineer Remote jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Geospatial Data Engineer Remote jobs in Virginia look for? The top searched job categories for Geospatial Data Engineer Remote jobs in Virginia are:
What cities in Virginia are hiring for Geospatial Data Engineer Remote jobs? Cities in Virginia 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 Virginia as of July 2026, with employment types broken down into 1% As Needed, 83% Full Time, 13% Part Time, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.
Data Engineer

Data Engineer

Anika Systems

Leesburg, VA • On-site, Remote

$115K - $139K/yr

Full-time

Re-posted 17 days ago

Job description

Anika Systems is seeking a skilled Data Engineer to design, build, and optimize scalable data pipelines and platforms supporting federal clients. This role will play a critical part in enabling enterprise data strategies, supporting Office of the Chief Data Officer (OCDO) initiatives, and delivering high-quality, trusted data for analytics, reporting, and mission operations.
This opportunity is 100% remote.
The ideal candidate has hands-on experience with ETL/ELT pipelines, XBRL data processing, Apache Iceberg-based architectures, and advanced data optimization techniques such as materialized views and context-aware data engineering. This role also requires proficiency in AI tools and AI-assisted development workflows, along with experience building and deploying CI/CD pipelines for data and analytics platforms.
Key Responsibilities
Data Pipeline Development & ETL/ELT
  • Design, develop, and maintain robust ETL/ELT pipelines to ingest, transform, and deliver data across enterprise platforms.
  • Build scalable data ingestion frameworks for structured and semi-structured data, including XBRL filings and financial datasets.
  • Implement data transformation logic to support analytics, reporting, and regulatory use cases.
  • Ensure data pipelines are reliable, performant, and scalable in cloud environments.
  • Leverage AI-assisted development tools to accelerate pipeline development, testing, and optimization.
Cloud Data Platforms & Iceberg Architecture
  • Develop and manage data solutions leveraging AWS services (e.g., S3, Airflow, DAGs, Glue, Lambda, Redshift).
  • Implement and optimize Apache Iceberg table formats for large-scale, ACID-compliant data lakes.
  • Support lakehouse architectures that unify data lakes and data warehouses.
  • Optimize data storage and retrieval strategies for performance and cost efficiency.
  • Enable data platforms that support AI/ML workloads and downstream generative AI use cases.
CI/CD & DataOps Engineering
  • Design and implement CI/CD pipelines for data pipelines, infrastructure, and analytics code using tools such as GitHub Actions, GitLab CI, Jenkins, or AWS-native services.
  • Automate build, test, and deployment processes for ETL pipelines and data platform components.
  • Implement DataOps best practices, including version control, automated testing, environment promotion, and rollback strategies.
  • Ensure reproducibility, reliability, and governance of data pipeline deployments across environments.
  • Integrate AI-driven testing and monitoring tools to improve pipeline quality and reduce operational risk.
Data Optimization & Performance Engineering
  • Design and implement materialized views and other performance optimization techniques to improve query efficiency.
  • Tune data pipelines and queries for performance, scalability, and cost.
  • Implement partitioning, indexing, and caching strategies aligned to workload patterns.
XBRL & Financial Data Processing
  • Develop pipelines to ingest, parse, and normalize XBRL (eXtensible Business Reporting Language) data.
  • Support regulatory and financial data use cases requiring high accuracy and traceability.
  • Ensure alignment with data standards and validation rules for financial reporting datasets.
Context Engineering & Data Modeling Support
  • Apply context engineering principles to ensure data is enriched with meaningful metadata, lineage, and business context.
  • Collaborate with Data Architects to support data modeling, schema design, and entity relationships.
  • Enable downstream analytics and AI use cases by structuring data for usability, discoverability, and governance.
Metadata, Data Catalog, and Governance Integration
  • Integrate pipelines with enterprise data catalogs and metadata management systems.
  • Support automated metadata capture, lineage tracking, and data quality monitoring.
  • Ensure alignment with data governance frameworks and standards established by OCDO organizations, including AI data readiness and traceability.
Stakeholder Collaboration & Agile Delivery
  • Collaborate with data architects, analysts, and business stakeholders to understand data needs and deliver solutions.
  • Participate in stakeholder listening campaigns, workshops, and data discovery efforts.
  • Work in Agile teams to iteratively deliver data capabilities and enhancements.
  • Contribute to identifying and implementing AI-driven efficiencies and automation opportunities across the data lifecycle.
Required Qualifications
  • Bachelor's degree in Computer Science, Engineering, Data Science, or related field.
  • 5+ years of experience in data engineering, ETL development, or data platform engineering.
  • Strong hands-on experience with:
    • ETL/ELT tools and frameworks
    • AWS data services (S3, Glue, Lambda, Redshift, etc.)
    • Apache Iceberg and modern data lake architectures
  • Experience designing and implementing CI/CD pipelines for data platforms and ETL workflows.
  • Demonstrated proficiency using AI tools and AI-assisted development workflows (e.g., LLM copilots, automated code generation, pipeline optimization tools).
  • Experience processing XBRL or complex financial/regulatory datasets.
  • Proficiency in SQL and Python.
  • Experience implementing materialized views and query optimization techniques.
  • Understanding of data modeling concepts and metadata management.
  • Familiarity with data governance, data quality practices, and data readiness for AI/ML use cases.
  • Ability to work in Agile, DevOps-oriented environments.
  • U.S. Citizenship required; ability to obtain and maintain a federal clearance.
Preferred Qualifications
  • Experience supporting federal agencies such as SEC, DHS, Treasury, or Federal Reserve System.
  • Familiarity with data catalog tools (e.g., Collibra, Alation, ServiceNow).
  • Experience with Apache Spark, Kafka, or other distributed data processing frameworks.
  • Experience enabling data pipelines for AI/ML or generative AI applications.
  • Knowledge of data maturity frameworks (e.g., EDM DCAM, TDWI).
  • Exposure to context engineering or semantic data layer design.
  • AWS or data engineering certifications.
  • Experience with infrastructure-as-code (IaC) tools (e.g., Terraform, CloudFormation) in support of CI/CD pipelines.

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