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Remote Dlp Engineer Jobs in Virginia (NOW HIRING)

Ad Hoc

Evergreen: Senior Network/Security Engineer

Mclean, VA · Remote

$59.25 - $77.25/hr

Senior Network/Security Engineer Job number: 793 This is a remote position. Ad Hoc is a technology ... Upgrade the DLP plug-in so it works cleanly in SCM Preferred Qualifications: * Current or previous ...

United Airlines

Senior Cloud Engineer

Mclean, VA · On-site +1

$70K - $144K/yr

Location Remote based role with preference in Hub Office City. About The Job You're Considering ... Secure M365 workloads with a strong focus on tenant hardening, conditional access, DLP, and insider ...

SAIC

Senior Power Platform Developer

Arlington, VA · Remote

$62.75 - $82.75/hr

TS/SCI Potential for Remote Work: ORA_HYBRID Description SAIC is seeking a Senior Power Platform ... prevention (DLP) policies. and innovative IT service delivery enhancements. End-User Support:

Booz Allen Hamilton, Inc.

Zero Trust Architect

Mclean, VA · On-site +1

$77K - $176K/yr

Remote Work: Hybrid Job Number: R0234025 Location: McLean,VA,US Share job via: Share Zero Trust ... What if you could use your cyber engineering skills to design and build secure systems for the U.S.

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Remote Dlp Engineer information

What are Remote DLP Engineers?

Remote DLP (Data Loss Prevention) Engineers are IT professionals who specialize in designing, implementing, and managing DLP solutions to protect sensitive data from unauthorized access or leaks, while working remotely. They configure security tools, monitor data movement, and respond to potential threats to ensure compliance with data protection regulations. By working offsite, they collaborate with teams using digital communication tools and maintain the security posture of their organization's information assets. Their expertise is critical for companies with distributed workforces and cloud-based environments.

What are the key skills and qualifications needed to thrive as a Remote DLP Engineer, and why are they important?

To thrive as a Remote DLP Engineer, you need deep expertise in data loss prevention strategies, information security principles, and a background in computer science or a related field. Familiarity with DLP solutions like Symantec, Forcepoint, or Microsoft Information Protection, as well as relevant certifications such as CISSP or CISM, is commonly required. Strong analytical thinking, problem-solving skills, and clear communication set top candidates apart, especially when collaborating with distributed teams. These skills ensure effective protection of sensitive data, compliance with regulations, and smooth incident response in a remote work environment.

What are some common challenges faced by Remote DLP Engineers, and how can they be effectively managed?

Remote DLP (Data Loss Prevention) Engineers often face challenges such as ensuring consistent policy enforcement across distributed endpoints and managing security incidents without direct on-premise access. Communication with cross-functional teams, such as IT support and compliance, is key to quickly resolving issues and maintaining data security standards. Leveraging advanced monitoring tools, automating routine tasks, and participating in regular virtual meetings can help address these challenges, ensuring the DLP program remains effective and responsive in a remote environment.

What is the difference between Remote Dlp Engineer vs Data Security Analyst?

AspectRemote Dlp EngineerData Security Analyst
Required CredentialsBachelor's in CS or related, certifications like CISA or GIACBachelor's in IT, Cybersecurity, or related, similar certifications
Work EnvironmentIT/security teams, remote or on-site, technical focusSecurity teams, often remote, analytical and monitoring focus
Employer & IndustryTech, finance, healthcare, companies with data protection needsFinancial institutions, healthcare, government agencies

While both roles focus on data security, Remote Dlp Engineers primarily develop and implement data loss prevention solutions, whereas Data Security Analysts monitor and analyze security threats. The roles often overlap in certifications and work environments, but their core responsibilities differ in technical implementation versus threat analysis.

What are popular job titles related to Remote Dlp Engineer jobs in Virginia? For Remote Dlp Engineer jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Remote Dlp Engineer jobs in Virginia look for? The top searched job categories for Remote Dlp Engineer jobs in Virginia are:
What cities in Virginia are hiring for Remote Dlp Engineer jobs? Cities in Virginia with the most Remote Dlp Engineer job openings:
Remote Dlp Engineer jobs near you
Infographic showing various Remote Dlp Engineer job openings in Virginia as of July 2026, with employment types broken down into 81% Full Time, and 19% Contract. Highlights an 100% Remote job distribution.

SENIOR AI DATA INTEGRATION ENGINEER

Northhill Technology

Mclean, VA • On-site, Remote

$105K - $145K/yr

Full-time

Posted 8 days ago

Job description

NorthHill Technology Resources has an urgent need for a Senior Data Integration Engineer for a cutting-edge opportunity in Mclean, VA.This is a direct-hire role with our client, a highly respected banking organization,It is a hybrid role, with 3 days onsite and 2 remote per week.
Position Summary
Own the bank's approved knowledge and systems layer for AI by implementing secure grounding on enterprise content, approved connectors, permissions-aware retrieval, and DLP-aligned data handling. This role includes the immediate masking and unmasking path for SharePoint-accessed content using Presidio and Protect.
Core Responsibilities
  • Build and maintain secure grounding patterns for approved content repositories and internal business systems, starting with SharePoint and other governed enterprise sources.
  • Implement approved connectors and retrieval workflows with permissions-aware access, source traceability, and controls that scope retrieval to the minimum necessary data.
  • Implement and support Presidio and Protect for immediate masking and unmasking of SharePoint-accessed content before it is released to approved AI workflows.
  • Partner with Security, IT, Information Governance, and business owners on DLP, sensitivity labels, metadata, redaction, and data-handling controls for AI retrieval paths.
  • Improve retrieval quality, metadata standards, and integration reliability across structured and unstructured sources so answers remain grounded and supportable.
  • Create reusable onboarding standards for new content sources, including access review, logging expectations, retention considerations, and validation before activation.
  • Engineer retrieval services that preserve permissions inheritance and return provenance metadata sufficient to support reviewer verification, citations, and audit traceability.
  • Build validation checklists for new repositories, connectors, content types, and SharePoint masking flows before they are exposed to employee-facing copilots or higher-risk governed workflows.
  • Partner with Guardrails and Application teams to tune retrieval quality, reduce hallucination risk, and enforce least-privilege data access across approved workflows.
  • Support secure integration patterns for approved enterprise AI platforms, including Claude Cowork and related retrieval-dependent tools, where grounding, connector behavior, provenance controls, and masking services must be enforced.

Control Requirements
  • Implement connector and retrieval logging that supports audit trails for what data sources were accessed, by whom, and under what approved workflow where the platform supports it.
  • Design integrations to respect data minimization, permissions inheritance, read-only access where required, and restrictions on shared file write or delete behavior.
  • Help operationalize immediate compensating controls for PII or NPI workflows, including Presidio and Protect for SharePoint-accessed content, with documented fallback redaction controls and QA where needed.
  • Coordinate evidence and metadata standards so approval artifacts, retrieval traces, and content-source onboarding records can be retained in the governance repository.
  • Contribute technical review for plugins, custom MCP servers, and other integrations that expose enterprise systems to AI workflows.

Required Qualifications
  • 6+ years in data engineering, integrations, enterprise search, retrieval engineering, knowledge systems, or content-platform engineering.
  • Hands-on experience with APIs, enterprise content platforms, permissions models, identity-aware retrieval, and reliable integration patterns across heterogeneous data sources.
  • Strong understanding of data classification, DLP concepts, metadata, lifecycle and retention considerations, and enterprise content governance.
  • Ability to troubleshoot retrieval quality, indexing, connector reliability, and source traceability in document-heavy environments.
  • Experience documenting standards so new data sources can be onboarded repeatedly without creating inconsistent control behavior.

Preferred Qualifications and Skills
  • Experience with SharePoint, Microsoft Graph, Copilot Studio grounding patterns, semantic search, vector or hybrid retrieval, and enterprise content systems used in regulated environments.
  • Exposure to legal, trust, compliance, HR, or document-heavy operational processes where permissions and provenance matter.
  • Financial services or other regulated-data experience with practical awareness of privacy, records, and audit obligations.
  • Hands-on experience with Presidio, Protect, or comparable masking, redaction, and data-protection tooling that can support controlled AI workflows.
  • Experience supporting Claude Cowork or similar enterprise AI platforms where retrieval, knowledge access, and provenance controls matter.
  • Familiarity with Claude Code or comparable AI-assisted engineering tools for connector development, debugging, and integration acceleration.

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