Senior Systems Architect / Data Engineer

Peraton•Augusta, GA

6d•$146,000 - $234,000

About The Position

Peraton is seeking a Senior Systems Architect / Data Engineer to lead the design and implementation of enterprise-scale cloud data solutions supporting the ARCYBER Platform Management Support project. This role ensures cloud-native pipelines, storage, governance, and access frameworks are designed for performance, scalability, and compliance. The position involves architecting and supporting cloud-native data systems on AWS, developing data parsers, designing large-scale pipelines, collaborating with customers to translate mission requirements, optimizing data storage, implementing schema standards, supporting enterprise architecture efforts, mentoring junior engineers, leading data feed onboarding and production support, driving schema standardization and data transformation, and supporting JCWA platform enhancements. The role also requires applying Agile delivery practices using Jira, GitLab, and CI/CD workflows.

Requirements

Bachelor’s degree in Computer Science, Systems Engineering, or related field and 12+ years of experience, 10 years with MS, or 7 years with PhD. Will consider AA with 14+ years or HS with 16+years.
Experience developing and supporting AWS-based data systems using cloud storage, compute, IAM-enabled access patterns, and secure data movement concepts.
Proficient development experience in Java, and Python.
Experience with data pipeline and data movement technologies such as Kafka, Confluent, Apache NiFi, Spark, Prefect, or Airflow.
Proficient with SQL and PostgreSQL, including data modeling, query optimization, schema design, and supporting analytics-ready data structures.
Experience deploying, operating, or troubleshooting data services in containerized environments using Docker and Kubernetes.
Experience documenting data workflows, schemas, interface requirements, data mappings, and operational processes.
Ability to collaborate directly with customers, engineers, analysts, and cross-functional stakeholders to translate mission requirements into technical data solutions.
Experience with metadata cataloging, data governance processes, data lineage, or data quality management.
Active TS SCI with ability to obtain Polygraph, and MEAD clearance.
U.S Citizenship required.

Nice To Haves

Familiarity with Elastic Stack, Elastic Common Schema (ECS), or similar schema governance and observability frameworks.
Familiarity with Bash scripting, AWS CLI, and automation for troubleshooting or operational support.
Experience with NoSQL databases, data warehousing strategies, or hybrid SQL/NoSQL storage patterns.
Cloud certifications (AWS Solutions Architect, AWS Data Engineering, or equivalent).
Experience with DevSecOps, Infrastructure-as-Code (like Terraform/CloudFormation), and CI/CD pipelines (GitHub/GitLab).
IAT Level II certification (Sec+) or higher.

Responsibilities

Architect and support cloud-native data systems on AWS, including compute (EC2), storage (S3), and IAM.
Develop and maintain data parsers (primarily in Java, with Python for scripting/automation) for structured and unstructured sources.
Design and maintain large-scale pipelines leveraging Kafka, Apache NiFi, and containerized environments (Docker/Kubernetes).
Collaborate with customers to translate mission requirements into scalable, cloud-based data workflows.
Optimize data storage (SQL and NoSQL) for performance, scalability, and governance.
Implement schema standards (e.g., Elastic Common Schema) and metadata cataloging to ensure consistency across diverse sources.
Support enterprise architecture efforts, conducting gap analyses (comparing current and target state architectures) and proposing solutions.
Mentor junior engineers and enforce best practices in version control, CI/CD, and documentation.
Lead data feed onboarding, pipeline operations, and production support across cloud-based data workflows.
Drive schema standardization, parser enhancement, data transformation, and data structure lifecycle management.
Support JCWA platform enhancements through data integration, workflow optimization, and architecture alignment.
Apply Agile delivery practices using Jira, GitLab, and CI/CD workflows to improve team execution and transparency.