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Remote Data Aggregation Jobs in Virginia (NOW HIRING)

VTG

Software Engineer

Chantilly, VA · Remote

Develop aggregation operations to de-duplicate records across continuous data feeds. * Build and ... Bachelor's degree in Geospatial Intelligence, Geography, Remote Sensing, Intelligence Studies ...

VTG

Software Engineer

Chantilly, VA · Remote

Develop aggregation operations to de-duplicate records across continuous data feeds. * Build and ... Bachelor's degree in Geospatial Intelligence, Geography, Remote Sensing, Intelligence Studies ...

Imh

... remote but must travel as needed for mandatory meetings, site visits and go-lives | Schedule ... Aggregate of equipment/hardware/data connection forecasts and mapping of new construction ...

New

Maximus

DevSecOps Engineer

VA · On-site +1

General information Job Posting Title DevSecOps Engineer Date Friday, April 3, 2026 City Remote ... data analysis of network security, remediation patching coordination, and compliance efforts ...

ICF

Senior DevOps Engineer - (US - Remote)

Reston, VA · Remote

$135K - $173K/yr

In this position, you will be part of the team building best in class enterprise data analytics ... Implement application metrics collection and log aggregation to provide continuous monitoring ...

Veilant

Technical Project Manager

Mclean, VA

Preferred Skills - Knowledge of Microsoft Office Suite including Word, Excel, Outlook, PowerPoint and Project - Critical thinking and effective independent data analysis skills - Excellent oral and ...

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Remote Data Aggregation information

What is the difference between Remote Data Aggregation vs Remote Data Analyst?

AspectRemote Data AggregationRemote Data Analyst
Required CredentialsBasic data handling skills, familiarity with data toolsBachelor's in Data Science, Statistics, or related field; often requires certifications
Work EnvironmentPrimarily technical, focused on data collection and processingAnalytical, interpretative, and reporting-focused
Employer & Industry UsageUsed across industries for consolidating data sourcesCommon in finance, marketing, healthcare for insights
Search & Comparison IntentUnderstanding data collection rolesAnalyzing data to inform decisions

Remote Data Aggregation involves collecting and consolidating data from various sources, focusing on data collection and management. Remote Data Analysts interpret and analyze data to generate insights, often requiring more specialized education and analytical skills. Both roles are essential in data-driven industries but serve different functions within the data lifecycle.

What is remote data aggregation?

Remote data aggregation is the process of collecting, compiling, and organizing data from various sources without being physically present at a central location. Professionals in this field use digital tools and software to access, extract, and consolidate information from databases, websites, or third-party platforms. This role is essential for businesses that rely on real-time or large-scale data from multiple sources, as it enables efficient analysis and reporting. Remote data aggregation is commonly utilized in industries such as market research, finance, and e-commerce, where timely and accurate data is crucial for decision-making.

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

To thrive as a Remote Data Aggregation Specialist, you need strong analytical skills, attention to detail, and proficiency in data management, often supported by a degree in information technology, statistics, or a related field. Familiarity with data aggregation tools, database systems (such as SQL), and spreadsheet software like Excel is typically required. Excellent organizational skills, self-motivation, and effective communication are important soft skills for collaborating remotely and ensuring accurate results. These skills and qualities are essential for efficiently collecting, organizing, and delivering high-quality data that supports business decision-making.

What are some common challenges faced by professionals in remote data aggregation roles, and how can they be addressed?

Remote data aggregation professionals often encounter challenges such as inconsistent data sources, varying data formats, and communication barriers with distributed teams. These can be addressed by using robust data integration tools, establishing clear data validation protocols, and maintaining regular communication channels with colleagues and stakeholders. Staying adaptable and proactive in troubleshooting helps ensure data accuracy and timely project delivery. Additionally, ongoing training in new aggregation tools and methods can further streamline workflows.
What are the most commonly searched types of Data Aggregation jobs in Virginia? The most popular types of Data Aggregation jobs in Virginia are:
What are popular job titles related to Remote Data Aggregation jobs in Virginia? For Remote Data Aggregation jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Remote Data Aggregation jobs in Virginia look for? The top searched job categories for Remote Data Aggregation jobs in Virginia are:
What cities in Virginia are hiring for Remote Data Aggregation jobs? Cities in Virginia with the most Remote Data Aggregation job openings:
Remote Data Aggregation jobs near you
Infographic showing various Remote Data Aggregation job openings in Virginia as of June 2026, with employment types broken down into 83% Full Time, and 17% Contract. Highlights an 100% Remote job distribution.
Software Engineer with Security Clearance

Software Engineer with Security Clearance

VTG

Chantilly, VA • Remote

Other

Posted 27 days ago

Job description

Overview We are looking for a Software Engineer / Data Engineer to join our team. What will you do? * Design, build, and operate large-scale Big Data systems, including persistence, partitioning, indexing, and search capabilities.
  • Develop and maintain Java-based applications and APIs.
  • Architect and implement cloud-native solutions using AWS or comparable cloud platforms.
  • Design and optimize high-performance graph databases containing tens of billions of edges.
  • Develop graph traversal capabilities using Apache TinkerPop, Gremlin, JanusGraph, or similar technologies.
  • Build and maintain NoSQL and relational database solutions supporting complex Big Data applications.
  • Design partition and sort key strategies to ensure consistent system performance.
  • Develop aggregation operations to de-duplicate records across continuous data feeds.
  • Build and operate serverless data processing pipelines using AWS Lambda, Step Functions, and PySpark.
  • Design and operate large-scale geospatial indexing solutions using GeoMESA.
  • Develop and maintain Kubernetes-based containerized environments.
  • Implement DevSecOps and agile development practices in production environments.
  • Maintain configuration management using Git-based repositories.
  • Facilitate technical discussions across cross-functional teams to develop mission-aligned implementation strategies.
  • Ensure compliance with federal security, regulatory, and accreditation requirements.
Implement data security and governance controls including LDAP integration, encryption, and auditing. Do you have what it takes? Active TS/SCI with Polygraph required. * Bachelor's degree in Geospatial Intelligence, Geography, Remote Sensing, Intelligence Studies, Engineering, or related field, or equivalent experience
  • Demonstrated experience with Java development.
  • Experience designing and operating Big Data systems.
  • Experience developing and maintaining APIs.
  • Experience designing cloud-native architectures using AWS or similar cloud platforms.
  • Experience building and optimizing large-scale graph databases using technologies such as Cassandra, DynamoDB, Neo4j, or JanusGraph.
  • Experience developing graph traversal capabilities using Apache TinkerPop and Gremlin.
  • Experience designing and operating NoSQL solutions.
  • Experience in data modeling, partition sharding, stream processing, and metrics gathering.
  • Experience developing high-performance data processing pipelines.
  • Experience with Kubernetes, Docker, and container orchestration.
  • Experience with Apache NiFi.
  • Experience implementing DevSecOps and agile methodologies.
  • Experience with data security controls including encryption and centralized access management (LDAP).
  • Experience working with structured, semi-structured, and unstructured data formats (CSV, JSON, AVRO, Parquet, Protocol Buffers, etc.).
  • Experience with relational and NoSQL databases including PostgreSQL, MariaDB, MongoDB, Cassandra, ELK, MinIO, and AWS S3.
  • Experience working in Linux environments such as CentOS or Rocky Linux.
  • Experience with Python and related libraries.
  • Experience supporting large collaboration and development environments

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