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Job Description

Join CACI as a Senior Data Engineer on site in Reston, Virginia. You will design and implement scalable data solutions that support clients' LAN, WAN, and UC services, lead data integration and analytics enablement, and provide operational decision support for cybersecurity and network modernization.

CACI offers a comprehensive benefits package designed to support you and your family, including healthcare, wellness programs, financial and retirement benefits, family support, continuing education, time off, and ongoing learning opportunities.

Expect a culture built on integrity and trust, with a clear focus on continuous growth.

Responsibilities

  • Build and maintain end-to-end data pipelines for collecting, integrating, transforming, and storing data from multiple enterprise sources.
  • Design and govern scalable data architectures with layered storage β€” raw, staging, curated, and reporting-ready.
  • Create trusted, reusable datasets and structures that improve reporting consistency, dashboard performance, and analytics consumption.
  • Implement data quality controls, validation checks, monitoring, and alerts to detect schema changes, incomplete loads, and data freshness issues.
  • Troubleshoot complex issues across ingestion, transformation, and reporting workflows, identifying root causes and restoring trusted outputs.
  • Develop safe data publishing patterns, including staging-to-swap deployments, rerunnable processes, idempotent loads, and backfill strategies.
  • Collaborate with reporting and analytics stakeholders to prepare and optimize data structures for advanced analytics, machine learning, and visualizations.
  • Lead cross-functional data initiatives that improve visibility, reduce manual effort, and strengthen data trust across operational workflows.
  • Conceptualize and implement data products, standards, and processes to enable future decision-support capabilities.
  • Stay current on advancements in data engineering, analytics architecture, data quality practices, and applied analytics methods.

Requirements

  • Active TS/SCI clearance with polygraph, or current TS/SCI clearance with the ability to obtain a polygraph prior to starting.
  • Bachelor's degree in data science, computer science, statistics, mathematics, engineering, information systems, or a related field.
  • 10+ years of related experience as a Data Engineer, Analytics Engineer, Data Scientist, or similar role.
  • Current DoD 8570 IAT Level II certification (for example Security+ CE).
  • Strong understanding of data governance, access control, and security best practices in regulated or sensitive environments.
  • Proficiency in Python and SQL for data manipulation, pipeline development, data validation, and analytics support.
  • Extensive hands-on experience designing and maintaining scalable data architectures, databases, and automated data engineering workflows.
  • Experience with database platforms including schema design, performance optimization, views and materialized views, and data modeling.
  • Proven ability to investigate complex data issues, perform root-cause analysis, and implement sustainable corrective actions.
  • Experience developing technical standards, improving workflow reliability, and communicating technical issues and recommendations to leadership and stakeholders.

Technologies

  • Python
  • SQL
  • Tableau

Benefits

  • Healthcare
  • Wellness
  • Financial benefits
  • Retirement benefits
  • Family support
  • Continuing education
  • Time off benefits
  • Learning and development opportunities

What you can expect

  • A culture of integrity.
  • An environment of trust.
  • A focus on continuous growth.

Compensation

Salary range: $105,100 to $231,100 per year. Final compensation depends on location, federal contract labor categories and contract wage rates, relevant prior work experience, specific skills and competencies, education, and certifications. Because this position may be located in multiple locations, the range shown reflects the national average for the role.

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