Data Manager

Peraton; Maryland; On-site; USD 70,000 - 90,000; Full time

Job summary

Peraton is seeking a Data Analyst to support customer operations onsite in Bethesda, MD. This role involves managing and integrating enterprise data, ensuring that it is accessible and meets operational objectives, especially as data complexity increases.

The successful candidate will implement data standards and governance policies, maintain lifecycle processes, and support configuration management efforts. Strong analytical skills and experience with data management tools are essential for this position.

Qualifications

• 8+ years of experience supporting data management, data governance, or enterprise data environments.
• TS/SCI with Polygraph clearance required.
• Experience with configuration management principles and documentation governance.

Responsibilities

• Establish, maintain, and improve enterprise data lifecycle processes.
• Support enterprise data governance initiatives.
• Conduct data quality assessments and implement standardized processes.

Skills

Data management and analysis tools (SQL, Python, Excel, Access)

Strong written and verbal communication skills

Ability to analyze data-related processes

Education

BA/BS or equivalent years of experience

Tools

Jira

Confluence

Job description

Required

• Requires BA/BS and 8+ years of experience supporting data management, data governance, data integration, or enterprise data environments; or no degree and 12+ years of relevant experience.
• TS/SCI with Polygraph clearance required.
• Experience supporting enterprise data lifecycle management processes and data governance initiatives.
• Experience with data integration, interoperability, metadata management, and repository administration.
• Knowledge of configuration management principles, version control practices, and documentation governance.
• Experience developing and maintaining technical documentation, reports, and briefing materials.
• Proficiency with data management and analysis tools such as SQL, Python, Excel, Access, or equivalent technologies.
• Experience supporting enterprise data repositories, storage environments, or data management platforms.
• Ability to analyze data-related processes and recommend improvements to data quality, accessibility, and operational efficiency.
• Strong written and verbal communication skills with the ability to present technical concepts to diverse stakeholder audiences.
• Demonstrated ability to work independently and collaboratively within a fast-paced mission environment.

Desired Qualifications

• Experience supporting Intelligence Community programs or other federal government environments.
• Familiarity with data governance frameworks, metadata standards, and enterprise data management best practices.
• Hands‑on experience with Jira, Confluence, or other collaboration and configuration management tools.
• Experience supporting cloud-based data environments and enterprise storage architectures.
• Familiarity with automation processes that improve data validation, ingestion, and reporting workflows.
• Experience supporting configuration control boards, technical review processes, or engineering documentation management.
• Understanding of enterprise interoperability standards and data exchange methodologies.
• Experience with the following Work Products preferred:
  • Data Management Lifecycle Documentation
  • Data Governance and Quality Plans
  • Data Integration and Interoperability Plans
  • Data Repository and Infrastructure Documentation
  • Configuration Management and Documentation Review Reports
  • Data Standards and Architecture Recommendations
  • Data Performance and Reliability Reports

Peraton is seeking a Data Analyst to support our customer onsite in Bethesda, MD. The Data Analyst will support enterprise data management, integration, governance, and configuration management activities across the program. This role is responsible for ensuring enterprise data is structured, accessible, reliable, and aligned with mission and operational objectives as data volume, complexity, and interoperability requirements continue to evolve.

The successful candidate will establish and maintain data lifecycle processes, support integration and interoperability across systems, and assist with implementing data standards, governance policies, and repository management practices. This position will also support configuration management efforts through controlled reviews of technical and engineering documentation to ensure consistency, traceability, and version control across enterprise data assets and systems.

Responsibilities

• Establish, maintain, and improve enterprise data lifecycle processes, including data ingestion, storage, usage, archival, and retention practices.
• Support enterprise data governance initiatives by defining and maintaining data standards, validation rules, metadata management practices, and quality control procedures.
• Integrate disparate data sources and artifacts across federated systems to support interoperability and mission requirements.
• Support the development, maintenance, and optimization of enterprise data repositories and storage environments.
• Conduct data quality assessments and implement standardized processes to improve data reliability and minimize manual intervention.
• Perform configuration management and controlled documentation reviews to ensure alignment, traceability, consistency, and version control across data assets and engineering documentation.
• Analyze enterprise data structures, policies, and workflows to identify opportunities for improved accessibility, efficiency, and reliability.
• Develop and maintain documentation, reports, briefing materials, and technical artifacts related to data governance, repository management, and integration activities.
• Support integration of new data models, standards, schemas, and artifacts into existing enterprise environments.
• Collaborate with engineering, operations, and stakeholder teams to support evolving mission and program data requirements.
• Provide recommendations to improve enterprise data architecture, governance policies, interoperability standards, and repository performance.
• Communicate technical findings and recommendations clearly through written documentation, visual presentations, and verbal briefings suitable for both technical and non-technical audiences.