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Data Collector Jobs in Vienna, VA (NOW HIRING)

MartinFed

SIEM Data Engineer (DoD TS Clearance)

Arlington, VA · On-site

$131K - $158K/yr

Develop data ingestion strategies and onboard new log and event sources using inputs, forwarders, HTTP Event Collector (HEC), and API-based integrations. * Configure and validate data inputs across ...

Posted today

Element Materials Technology

Data Processor

Adelphi, MD · On-site

Element has an opportunity for a Data Processor to join our rapidly expanding team. As a member of the operations team in one of the various laboratories across Element, the Data Processer position ...

langan

Senior Biologist or Scientist

Arlington, VA · On-site

... data and preparing reports. In this role, you will have the opportunity to work cross ... Experience using GPS units in the field with use of ArcPad, Collector, Survey123 a plus;

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Data Collector information

See Vienna, VA salary details

$10

$20

$29

How much do data collector jobs pay per hour?

As of Aug 19, 2026, the average hourly pay for data collector in Vienna, VA is $20.28, according to ZipRecruiter salary data. Most workers in this role earn between $16.39 and $24.13 per hour, depending on experience, location, and employer.

What is a data collector?

As a data collector, you enter information into a database and ensure that your data collection sources are accurate. Your job duties include examining data, putting data points into a database, and using statistical software to create a data model, such as regression analysis. You need a high school diploma along with on-the-job training to start your career as a data collector. However, earning additional qualifications like a post-secondary certificate or an associate degree enables you to progress into more advanced jobs. You need excellent attention to detail and computer skills for this job as well.

What are the key skills and qualifications needed to thrive as a data collector?

To thrive as a Data Collector, you need strong attention to detail, organizational skills, and a basic understanding of data collection methodologies, often supported by a high school diploma or equivalent. Familiarity with data entry software, mobile data collection tools, and spreadsheet programs like Microsoft Excel is typically required. Excellent communication, reliability, and integrity are important soft skills, especially when interacting with participants or handling sensitive information. These skills ensure accurate, ethical, and efficient data gathering, which is critical for reliable research or business analysis.

What are some common challenges faced by data collectors in the field, and how can they be addressed?

Data Collectors often encounter challenges such as inconsistent data sources, limited access to information, and varying data quality. To overcome these, it’s important to follow standardized data collection procedures and maintain clear communication with supervisors and team members. Utilizing mobile data collection tools and regularly calibrating equipment can also improve efficiency and accuracy. Additionally, being adaptable and prepared for changing field conditions helps ensure reliable results.

What is the difference between Data Collector vs Data Analyst?

AspectData CollectorData Analyst
Required CredentialsHigh school diploma or equivalent; some roles may require certifications in data collection toolsBachelor's degree in data science, statistics, or related field; often requires analytical certifications
Work EnvironmentFieldwork, data entry, or office settings; often involves collecting data from surveys, sensors, or observationsOffice or remote work; analyzing data to generate reports and insights
Employer & Industry UsageResearch firms, government agencies, market research companiesBusiness, healthcare, finance, and technology sectors

While Data Collectors focus on gathering raw data from various sources, Data Analysts interpret and analyze this data to support decision-making. Both roles are essential in the data lifecycle but differ in their responsibilities and skill requirements.

How much money do data collectors make?

Data collectors typically earn between $10 and $20 per hour, depending on experience, location, and the complexity of the data collection tasks. Some positions may offer additional compensation for specialized skills or overtime work.

What kind of job is data collection?

A data collection job involves gathering, recording, and managing information from various sources for analysis or research purposes. It often requires attention to detail, organizational skills, and familiarity with data entry tools or software. Data collectors may work in fields like market research, healthcare, or social sciences, often following specific protocols or guidelines.
More about Data Collector jobs

What job categories do people searching Data Collector jobs in Vienna, VA look for?

The top searched job categories for Data Collector jobs in Vienna, VA are:

What cities near Vienna, VA are hiring for Data Collector jobs?

Cities near Vienna, VA with the most Data Collector job openings:

Data Collector jobs near you
Infographic showing various Data Collector job openings in Vienna, VA as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 13% Part Time, and 3% Contract. Highlights an 84% Physical, 5% Hybrid, and 11% Remote job distribution, with an average salary of $42,175 per year, or $20.3 per hour.

SIEM Data Engineer (DoD TS Clearance)

MartinFed

Arlington, VA • On-site

$131K - $158K/yr

Full-time

Posted 11 hours ago

Posted today

Job description

COMPANY OVERVIEW

Founded in 2007 in Huntsville, AL, MartinFed provides the U.S. government with customer-focused, performance-based solutions using technology and an empowered workforce as an engine to drive its customers' missions. Our goal is to attract the best and brightest within their field.

We invest in our people because they are our greatest asset. They cultivate our purpose, embody and reflect our core values, and define our culture. MartinFed's core values that set us apart are the following:

  • Be Driven - We are fueled by the hunger to learn more and do more.
  • Be Curious - We engage in continuous improvement - never accepting the status quo.
  • Be Humble - We seek honest feedback to strengthen our relationships.
  • Pursue Excellence - We strive to achieve extraordinary results and do not settle for mediocrity.

Strive for excellence and consider joining our growing team today!

JOB OVERVIEW

The SIEM Data Engineer is responsible for the ingestion, parsing, normalization, and quality of data flowing into the Splunk platform across government agencies. This role owns the data pipeline - from onboarding new log and event sources to ensuring data is accurate, consistent, and normalized to a common schema so it is immediately usable for analysis and detection. The Data Engineer works closely with the Platform Engineer, Detection Engineer, and source-system owners to deliver reliable, high-quality data.

Essential Functions:

  • Data Ingestion and Source Onboarding
    • Develop data ingestion strategies and onboard new log and event sources using inputs, forwarders, HTTP Event Collector (HEC), and API-based integrations.
    • Configure and validate data inputs across diverse log and event data types.
  • Parsing and Field Extraction
    • Develop and maintain parsing configurations (props.conf, transforms.conf) including field extractions, event breaking, and timestamp recognition.
    • Build and tune regular expressions to accurately extract fields from structured and unstructured data.
  • Data Normalization
    • Design and implement data normalization to the Splunk Common Information Model (CIM) for consistent, cross-source analysis.
    • Ensure data conforms to standardized schemas that support downstream reporting and detection.
  • Data Quality and Monitoring
    • Monitor data feeds for gaps, latency, volume anomalies, and parsing errors, and remediate issues quickly.
    • Establish data validation and quality checks to maintain accuracy and completeness.
  • Source Integration
    • Integrate data from on-premises, cloud, and third-party systems, coordinating with source owners on formats and connectivity.
    • Partner with the Platform Engineer on index and sourcetype design to optimize storage and searchability.
  • Data Lifecycle and Compliance
    • Apply retention, masking, and handling requirements to ingested data in line with relevant standards and regulations.
    • Support compliance and audit needs related to data provenance and integrity.
  • Documentation
    • Maintain documentation of data sources, onboarding procedures, parsing logic, and data flows.
    • Create runbooks to support consistent, repeatable data onboarding.

Qualifications:

  • US Citizen with an active Top Secret Security Clearance.
  • Bachelor's degree in Computer Science or a related field plus 6 years of related experience.
  • Proven experience with Splunk data onboarding, parsing, and normalization, preferably within government or enterprise environments.
  • Hands-on experience with props.conf/transforms.conf, field extractions, and the Splunk Common Information Model (CIM).
  • Strong proficiency with regular expressions and a solid understanding of log formats (syslog, JSON, CSV, Windows Event Log, cloud audit logs, etc.).
  • Understanding of data pipeline concepts, data quality, and log management principles.
  • Excellent problem-solving skills and the ability to diagnose and resolve data quality and ingestion issues.
  • Strong written and verbal communication skills.

DESIRED:

  • Data onboarding via inputs, universal/heavy forwarders, HEC, and API/scripted inputs
  • Parsing and event processing: props.conf/transforms.conf, event breaking, timestamp recognition, line merging
  • Field extraction and strong regular expression proficiency
  • Data normalization to the Splunk Common Information Model (CIM)
  • Sourcetype, index, and knowledge object design in coordination with the platform team
  • Data quality monitoring: gap/latency detection, volume anomaly identification, and remediation
  • Deep familiarity with common log formats (syslog, JSON, CSV, Windows Event Log, cloud audit logs, network/EDR telemetry)
  • Data pipeline and integration experience across on-prem, cloud, and third-party sources
  • Scripting (Python and/or Bash) for automation and data validation

PHYSICAL REQUIREMENTS & ENVIRONMENTAL CONDITIONS

  • Inside office environment.
  • Working on a computer for long periods of time.
  • May involve long period of sitting at a desk.
  • The work environment is fast-paced and sometimes involves extreme deadline pressures.

OTHER DUTIES

This job description is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities that are required of the employee for this job. Duties, responsibilities, and activities may change at any time with or without notice.


MartinFed is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regards to race, color, religion, religious creed, gender, sexual orientation, gender identity, gender expression, transgender, pregnancy, marital status, national origin, ancestry, citizenship status, age, disability, protected Veteran Status, genetics or any other characteristics protected by applicable federal, state or local law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. In addition to federal law requirements, MartinFed complies with all applicable state and local laws governing nondiscrimination in all locations.

If you are a qualified individual with a disability or disabled veteran, you have the right to request a reasonable accommodation if you are unable or limited in your ability to use or access MartinFed's current openings as a result of your disability. You can request reasonable accommodations by calling 855.212.1810. Thank you for your interest in MartinFed.


Please Note: All positions at MartinFed are contingent upon passing a background check prior to a start date and are subject to random drug screenings during the employment period. In addition, MartinFed is an E-Verify employer.

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