Data Engineer with Top Secret clearance

Peraton; Washington (District of Columbia); On-site; USD 150,000 - 210,000; Full time

Job summary

Peraton in Washington, DC seeks an experienced Data Engineer SME to lead design, development, and integration of enterprise data pipelines, APIs, and data-sharing services across complex environments.

You will collaborate with government stakeholders, data architects, and engineers to translate mission requirements into scalable data architectures, ensuring security, interoperability, and reliable data delivery across organizational boundaries.

Qualifications

• Bachelor's degree or equivalent in a technical discipline.
• 12+ years in data engineering, data integration, or software engineering with advanced degrees.
• Active TS or higher clearance required; ability to obtain Q/SCI.
• Experience designing and developing enterprise data pipelines and integration solutions.
• Strong experience with RESTful data exchange and data services.
• Experience with data ingestion, transformation, normalization, validation, and delivery.
• Strong SQL skills with relational/analytical databases.
• Hands-on programming in Python, Java, or Scala.
• Experience integrating disparate data sources and platforms.
• Understanding of data interoperability, data modeling, and data standards.
• Experience developing data mappings, schemas, and interface specs.
• Experience with structured and unstructured data.

Responsibilities

• Provide technical leadership as Data Engineering SME across organizations and programs.
• Design, develop, test, deploy, and maintain scalable data pipelines and integration solutions.
• Develop and implement APIs, data exchange services, and integration capabilities.
• Create interoperability solutions across diverse data sources, systems, and platforms.
• Support data-sharing initiatives with DOE partners and IC organizations.
• Translate mission requirements into data engineering architectures and implementation plans.
• Collaborate with government stakeholders to define data requirements and interface specs.
• Develop reusable data interfaces and integration capabilities for multiple missions.
• Implement data ingestion, transformation, validation, enrichment, and delivery processes.
• Work with structured, semi-structured, and unstructured data environments.
• Build data services for both operational and analytical use cases.
• Integrate customer data assets with enterprise and external environments.
• Develop data mappings, schemas, and transformation logic.
• Incorporate data quality, validation, and monitoring in pipelines.

Skills

Data engineering

RESTful APIs

SQL

Python/Java/Scala

Data integration

Cloud platforms

Education

Bachelor's degree in CS or related field

MS/MA preferred

PhD welcome

Tools

Apache Kafka

Spark

Databricks

Airflow

NiFi

API gateways

Job description

Required Qualifications

• Bachelor's degree in Computer Science, Data Engineering, Information Systems, Software Engineering, Mathematics, Engineering, or a related technical discipline; equivalent experience may be considered.
• 12+ years of relevant experience in data engineering, data integration, software engineering, or a related discipline; Minimum of 10 years with MS/MA; Minimum of 7 years with Ph.D.
• Active TS or Q clearance or higher is required. Ability to obtain Q/SCI.
• Demonstrated experience designing and developing enterprise data pipelines and integration solutions.
• Strong experience developing and consuming RESTful APIs, data services, or other application/data exchange interfaces.
• Experience with data ingestion, transformation, normalization, validation, and delivery.
• Strong SQL skills and experience working with relational and/or analytical databases.
• Experience with Python, Java, Scala, or other modern programming languages used for data engineering.
• Experience integrating disparate data sources, systems, applications, and platforms.
• Understanding of data interoperability, data exchange, data modeling, data standards, and data-sharing concepts.
• Experience developing technical interface specifications, data mappings, schemas, and integration documentation.
• Experience working with structured and unstructured data.
• Demonstrated ability to translate mission and business requirements into technical data engineering solutions.
• Experience working across multiple organizations and collaborating with government and technical stakeholders.
• Strong analytical, problem-solving, communication, and technical documentation skills.
• Ability to work independently as a technical SME while collaborating effectively with multidisciplinary teams.

Preferred Qualifications

• Previous experience supporting the Intelligence Community, Department of Energy, or other U.S. Government mission environments.
• Experience developing data-sharing solutions between DOE and IC organizations.
• Experience supporting SIPP programs or related customer initiatives.
• Experience with government or enterprise data interoperability frameworks and data-sharing ecosystems.
• Experience designing and implementing enterprise API gateways, data exchange services, integration platforms, or data service architectures.
• Experience with cloud-based data engineering platforms, including AWS, Azure, or other government cloud environments.
• Experience with data lake, data warehouse, data lakehouse, or distributed data architectures.
• Experience with technologies such as Apache Kafka, Spark, Databricks, Airflow, NiFi, or equivalent data engineering platforms.

Position Overview

We are seeking an experienced Data Engineer / Subject Matter Expert (SME) to support a classified U.S. Government contract. The successful candidate will provide technical leadership in the design, development, implementation, and integration of enterprise data engineering capabilities supporting data interoperability, data exchange, data usage, and data sharing across complex customer environments.

The Data Engineer will design and develop data pipelines, APIs, data exchange services, integration services, and data interfaces that enable secure and reliable movement of data across customer systems and organizational boundaries. The position will support data-sharing initiatives with Department of Energy (DOE) partners, including IC organizations, and will work closely with government stakeholders, technical teams, mission partners, and external organizations.

The role will also support additional technical integration activities associated with DOE and SIPP programs, helping define and implement solutions for evolving data interface, data usage, interoperability, and data-sharing requirements. The ideal candidate will combine strong hands-on data engineering expertise with an enterprise perspective and the ability to develop practical solutions across diverse technical and organizational environments.

Key Responsibilities

• Serve as a Data Engineering SME providing technical leadership and expertise across customer organizations, mission areas, and data-sharing initiatives.
• Design, develop, test, deploy, and maintain scalable data pipelines and data integration solutions.
• Develop and implement APIs, data exchange services, integration services, and data interfaces supporting secure and reliable data sharing.
• Design technical solutions that enable interoperability across disparate data sources, systems, applications, platforms, and organizational environments.
• Support data-sharing initiatives between customer organizations and DOE partners, including Intelligence Community organizations.
• Translate customer and mission requirements into data engineering architectures, interfaces, pipelines, integration patterns, and technical implementation plans.
• Work with government stakeholders and technical teams to define data requirements, interface specifications, exchange mechanisms, and integration approaches.
• Develop reusable data interfaces and integration capabilities that can support multiple mission and organizational requirements.
• Implement data ingestion, transformation, normalization, validation, enrichment, and delivery processes.
• Develop solutions for structured, semi-structured, and unstructured data environments.
• Design and implement data services that support both operational and analytical use cases.
• Support the integration of customer data assets with enterprise, partner, and external data environments.
• Develop and maintain data mappings, schemas, data models, interface specifications, and transformation logic.
• Implement data quality, validation, monitoring, and error-handling capabilities within data pipelines and integration services.
• Identify and resolve technical challenges associated with data interoperability, data access, data exchange, and data sharing.
• Support DOE and SIPP programs with technical integration activities related to data interfaces, data usage, interoperability, and sharing requirements.
• Participate in technical architecture, design, and engineering activities supporting SIPP and related customer initiatives.
• Collaborate with data architects, data scientists, analysts, software developers, cybersecurity personnel, and mission stakeholders to deliver integrated data solutions.
• Coordinate with external customers, DOE organizations, IC partners, and other stakeholders to establish technical integration requirements and implementation approaches.
• Evaluate existing data interfaces and integration capabilities and recommend opportunities for modernization, standardization, and optimization.
• Support development and adoption of common data standards, exchange patterns, interface specifications, and reusable integration services.
• Develop technical documentation, including architecture diagrams, interface control documentation, API specifications, data mappings, data flows, and implementation plans.
• Support testing, validation, troubleshooting, and deployment of data integration capabilities across development and operational environments.
• Evaluate emerging data engineering and integration technologies and recommend solutions aligned with customer mission requirements.
• Support Agile and iterative engineering activities, including requirements development, technical design, development, testing, deployment, and sustainment.
• Ensure data engineering solutions comply with applicable security, classification, data governance, and customer requirements.