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Remote Lidar Data Processing Jobs in Washington (NOW HIRING)

Lovelytics

Lead Consultant, Data Engineer

Arlington, VA · On-site +1

$120K - $150K/yr

This role is open to remote candidates in the US. This role is not open for work sponsorship at ... Contribute to real-time data processing solutions and managed streaming data. * Implement security ...

Anika Systems

Data Engineer

Leesburg, VA · Remote

$115K - $139K/yr

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 ...

Edgesource

Data Engineer

Centreville, VA · On-site +1

$113K - $136K/yr

Optimize data processing and queries for performance and cost efficiency in AWS S3. * Exposure to ... Schedules (Remote / Hybrid) - - Medical / Dental / Vision / Flexible Spending Account (FSA ...

NT Concepts

Data Scientist

Herndon, VA · On-site +1

Herndon, VA with remote flexibility. Must be local to the DC Metro area. Responsibilities * Curate ... Experience building and maintaining ETL or data processing pipelines * Proficiency in Python and ...

Addison Group

Senior Data Analyst

Washington, DC · Remote

$135K - $150K/yr

Remote Job Type: Full-Time | Exempt Salary: $135,000 - $150,000 / Year Benefits: This position is ... Supports the Informatics department and develops business processes and systems to ensure integrity ...

Addison Group

Senior Data Analyst

Washington, DC · Remote

$135K - $150K/yr

Remote Job Type: Full-Time | Exempt Salary: $135,000 - $150,000 / Year Benefits: This position is ... Supports the Informatics department and develops business processes and systems to ensure integrity ...

System One

Data Scientist

Mclean, VA · Remote

Remote Hours: 40.0 Clearance: Must be eligible to obtain a US Public Trust Contact: Crystal ... Natural Language Processing (NLP), Semantic search or information retrieval, Entity resolution or ...

System One

Data Scientist

Mclean, VA · Remote

Remote Hours: 40.0 Clearance: Must be eligible to obtain a US Public Trust Contact: Crystal ... Natural Language Processing (NLP), Semantic search or information retrieval, Entity resolution or ...

System One

Data Scientist

Mclean, VA · Remote

Remote Hours: 40.0 Clearance: Must be eligible to obtain a US Public Trust Contact: Crystal ... Natural Language Processing (NLP), Semantic search or information retrieval, Entity resolution or ...

System One

Data Scientist

Mclean, VA · Remote

Remote Hours: 40.0 Clearance: Must be eligible to obtain a US Public Trust Contact: Crystal ... Natural Language Processing (NLP), Semantic search or information retrieval, Entity resolution or ...

System One

Data Scientist

Mclean, VA · Remote

Remote Hours: 40.0 Clearance: Must be eligible to obtain a US Public Trust Contact: Crystal ... Natural Language Processing (NLP), Semantic search or information retrieval, Entity resolution or ...

System One

Data Scientist

Mclean, VA · Remote

Remote Hours: 40.0 Clearance: Must be eligible to obtain a US Public Trust Contact: Crystal ... Natural Language Processing (NLP), Semantic search or information retrieval, Entity resolution or ...

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Remote Lidar Data Processing information

What are some common challenges faced by professionals in remote Lidar data processing roles, and how can they be overcome?

Professionals working in remote Lidar data processing often encounter challenges such as managing large datasets, ensuring data accuracy, and troubleshooting software or hardware compatibility issues. Effective organization and use of cloud-based storage solutions can help handle large volumes of data efficiently. Additionally, staying up-to-date with the latest processing software and regularly participating in team meetings or online forums can aid in resolving technical problems and maintaining data quality. Proactive communication with team members also ensures smooth collaboration, even in a remote work setting.

What is remote LiDAR data processing?

Remote LiDAR data processing involves handling and analyzing LiDAR (Light Detection and Ranging) data from a location other than where the data was collected. Professionals use specialized software to process large datasets, extract features like terrain models or vegetation, and generate 2D or 3D representations of landscapes. This remote work setup allows teams to collaborate globally, efficiently process data for industries like mapping, forestry, and urban planning, and deliver results without being physically present at the survey site.

What are the key skills and qualifications needed to thrive as a Remote Lidar Data Processing Specialist, and why are they important?

To thrive as a Remote Lidar Data Processing Specialist, you need a solid background in geospatial sciences, data analysis, and remote sensing, often supported by a relevant degree such as geography, GIS, or engineering. Familiarity with specialized software like LAStools, ArcGIS, and Global Mapper, as well as experience with data formats such as LAS and point cloud processing, is typically required. Strong problem-solving skills, attention to detail, and effective communication are essential soft skills for ensuring data accuracy and collaborating with team members. These skills and qualifications are important because they enable precise data interpretation, efficient workflow, and the delivery of high-quality geospatial products to clients.

What is the difference between Remote Lidar Data Processing vs Remote GIS Analyst?

AspectRemote Lidar Data ProcessingRemote GIS Analyst
Required CredentialsTypically requires GIS or remote sensing certifications, technical skills in lidar softwareRequires GIS certifications, spatial analysis skills, and often a degree in geography or related field
Work EnvironmentPrimarily technical, focused on lidar data handling and processing softwareMore analytical, involving spatial data analysis, mapping, and reporting
Industry UsageUsed in surveying, mapping, environmental monitoring, infrastructure planningApplied in urban planning, environmental management, resource allocation

Remote Lidar Data Processing focuses on handling and analyzing lidar point cloud data, while Remote GIS Analysts interpret spatial data for decision-making. Both roles require GIS knowledge but differ in technical focus and application areas.

What are popular job titles related to Remote Lidar Data Processing jobs in Washington? For Remote Lidar Data Processing jobs in Washington, the most frequently searched job titles are:
What job categories do people searching Remote Lidar Data Processing jobs in Washington look for? The top searched job categories for Remote Lidar Data Processing jobs in Washington are:
What cities in Washington are hiring for Remote Lidar Data Processing jobs? Cities in Washington with the most Remote Lidar Data Processing job openings:
Remote Lidar Data Processing jobs near you
Data Engineer - ML/AI Data Platform (Remote)

Data Engineer - ML/AI Data Platform (Remote)

FEI Systems

Columbia, MD • On-site, Remote

$111K - $133K/yr

Full-time

Posted 14 days ago

Job description

At FEI Systems, we create innovative technology solutions to improve the delivery of health and human services because we know when cumbersome administrative processes stand in the way, those who need it most are often left without access to proper care and support. From comprehensive case management software to disaster recovery services and content management information systems used in delivering foreign aid, our solutions are improving the lives of millions of people. We're looking for a data engineer who shares our commitment to leveraging technology to make a real impact in the world - a professional who knows, beyond all else, that the quality of our products and services is only as good as the company we keep.
All candidates will be required to complete at least one in-person interview as part of our hiring process.
Role Overview
We are seeking a Data Engineer to support Machine Learning and AI initiatives. Working closely with the Solution Architect, Data Architect, DevOps, and Application Engineering teams, this role is responsible for ensuring that data within our cloud-based platform is high quality, well-governed, feature-ready, and production-grade to support model training, deployment, and ongoing operations.
The ideal candidate has 5+ years of cloud data engineering experience with strong proficiency in Snowflake, Python, and SQL, and solid familiarity with AWS-native data services.
Candidates are not expected to arrive with expertise across every area listed. We are looking for demonstrated strength in the core data engineering and Snowflake skills, combined with the initiative and aptitude to grow into the broader scope of the role.
Day-One Priorities & Scope
Immediate focus is Snowflake-based data engineering, pipeline development, and data quality. Feature engineering, model training support, and MLOps contributions are growth areas that will ramp over time as you become embedded with the team.
Key Responsibilities
Data Pipeline Engineering
  • Design, build, and maintain scalable data pipelines supporting ML/AI workloads.
  • Engineer pipeline patterns including full loads, incremental loads, change-based loads, and slowly changing dimensions.
  • Ensure pipelines are reliable, performant, secure, and maintainable, troubleshoot and monitor pipelines within an AWS ecosystem.

Snowflake & Cloud Data Engineering
  • Perform data transformations in Snowflake using SQL and native Snowflake features.
  • Design and optimize schemas, tables, views, and materialized views for ML/AI consumption.
  • Support AWS-native data lake patterns using S3, Glue, Athena, Apache Iceberg, and S3 Tables.

Feature Engineering & Data Preparation
  • Perform data cleansing, normalization, and enrichment to support ML model development.
  • Design and implement feature engineering pipelines including aggregation and transformation.
  • Ensure consistency, reuse, and versioning of features across models and use cases.
  • Support feature store patterns to enable feature discoverability and reuse.
  • Collaborate with ML engineers and data scientists to operationalize features into training pipelines.

Model Training & MLOps Support
  • Support model training workflows, including dataset preparation and scheduled refreshes.
  • Ensure training datasets and features are reproducible, traceable, and auditable.
  • Integrate data pipelines into CI/CD workflows; support version control, testing, and deployment of data assets.
  • Monitor pipeline health, data freshness, and downstream impact on ML/AI systems.

Required Skills & Experience
5+ years of hands-on data engineering experience in a cloud environment.
Core Technologies
  • Python - strong proficiency for data processing and pipeline development.
  • SQL - advanced skills with hands-on Snowflake transformation experience.
  • Snowflake - ELT pipeline design, schema optimization, performance tuning, cost management.
  • PostgreSQL - experience with querying, data modeling, and analytics; familiarity with SQL Server to PostgreSQL migration a plus.
  • AWS - S3, Glue, Athena, Snowflake integration, and managed relational databases (e.g., Aurora, RDS).
  • Apache Iceberg / S3 Tables - familiarity with open table format ecosystems.
  • Streaming ingestion tools (e.g., Kinesis, Kafka, or equivalent).
  • Workflow orchestration tools (e.g., Airflow, Step Functions, or equivalent).

Pipeline & Data Engineering
  • Experience with full loads, incremental loads, append-only pipelines, change-based processing, and SCDs.
  • Data validation, reconciliation, error handling, and restart/recovery patterns.
  • Data modeling for analytics, ML/AI, and downstream application use cases.
  • Ability to evaluate pipeline design trade-offs across performance, cost, reliability, and maintainability.

DevOps & Engineering Practices
  • Structured SDLC experience with CI/CD pipelines for data and ML workflows.
  • API-based and event-driven data integration patterns.
  • Distributed data processing environments.

ML/AI Data Foundations
  • Understanding of data requirements for ML/AI workloads.
  • Experience preparing training datasets and features from enterprise data lakes.
  • Familiarity with reproducibility, dataset versioning, and data lineage concepts.
  • Familiarity with GenAI concepts relevant to data engineering, such as embedding pipelines, vector databases, retrieval-augmented generation (RAG) data flows, or prompt-driven data processing - including awareness of data security and privacy considerations when working with LLMs.

Education
Bachelor's degree in Computer Science, Data Engineering, Information Systems, or a related technical field. Equivalent professional experience will be considered.
Location: Remote
Status: Full time position with full company benefits.
NOTICE: EO/AA/VEVRAA/Disabled Employer - Federal Contractor. FEI Systems participates in E-Verify, a federal program that enables employers to verify the identity and employment eligibility of all persons hired to work in the United States by providing the Social Security Administration (SSA) and, if necessary, the Department of Homeland Security (DHS), with information from each new employee's Form I-9 to confirm work authorization. For more information on E-Verify, please contact DHS at (888) 464-4218.
Applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, marital status, political affiliation, disability, or genetic information, except where it relates to a bona fide occupational qualification or requirement. FEI Systems creates an Affirmative Action Plan on an annual basis. Pursuant to federal law, the portions of FEI Systems' Affirmative Action Program that relate to Section 503 (Persons with Disabilities) and/or Section 4212 (Protected Veterans), are available for inspection upon request by applicants and employees during FEI Systems' normal business hours.
Equal Opportunity Employer
This employer is required to notify all applicants of their rights pursuant to federal employment laws. For further information, please review the Know Your Rights notice from the Department of Labor.

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