Database Engineer

Peraton is seeking a Data Engineer with AI experience to support data modernization efforts for two existing business applications undergoing a major transformation. This position will be responsible for assisting with evaluating legacy data structures, designing modern data architectures, and enabling reliable, scalable, and secure data flows within the new modernization framework utilizing AI tools and methodologies. The ideal candidate has experience with enterprise data engineering, analytics, integration patterns, AI technologies, and cloud-based modernization initiatives.

Key Responsibilities

Data Architecture & Modernization Support

• Assist and support the design and implementation of modern data architectures that support the modernization framework, including data models, pipelines, and integration layers.
• Assess legacy systems to understand data structures, data quality, storage mechanisms, and transformation logic.
• Define strategies for data migration, data cleansing, normalization, and reconciliation between legacy and modernized systems.
• Help establish data standards, naming conventions, and governance practices for the modernized ecosystem.

Data Pipeline Development & Integration

• Assist with building and maintaining scalable data pipelines to support ingestion, transformation, and distribution of data across the modernized platform.
• Implement ETL/ELT solutions using modern data engineering tools and cloud services.
• Design APIs, streaming processes, and batch ingestion workflows as needed for system integration.
• Ensure data pipelines follow best practices for reliability, performance, and security.

Analytics & Business Insights

• Analyze legacy and modern data sets to identify inconsistencies, gaps, and transformation requirements.
• Work with business analysts and application teams to translate business needs into data requirements for the modernized applications.
• Create dashboards, reports, and analytic outputs to support modernization decision-making.

Collaboration

• Collaborate closely with architects, system developers, business analysts, and security teams to drive modernization goals.
• Participate in Agile ceremonies and contribute to planning and prioritization of modernization tasks.
• Identify data-related risks and issues.

Quality, Security, & Compliance

• Implement and enforce data validation, quality checks, and monitoring processes across pipelines.
• Support metadata management, data lineage, and data cataloging efforts.

AI Insight and Support

• Identify and implement opportunities to integrate artificial intelligence (AI) solutions throughout the Software Development Lifecycle (SDLC) and Dev Sec Ops processes.
• Identify and research AI-driven tools and methodologies to enhance automation, efficiency, and accuracy in areas such as code analysis, testing, security, and deployment pipelines.
• Collaborate with development and Dev Sec Ops teams to understand current workflows, identifying areas where AI can add value, and building or integrating AI solutions to streamline processes like vulnerability detection, performance optimization, or automated testing.

Required Qualifications

• 5 years with BS/BA; 3 years with MS/MA; 0 years with PhD
• Must be a U.S. Citizen
• Must have active Public Trust
• Experience in data engineering, data analytics, or related roles.
• Expert-level proficiency with SQL and experience working with relational and NoSQL databases.
• Experience building ETL/ELT pipelines and distributed data processing workflows.
• Hands-on experience with at least one modern data engineering stack.
• Experience with cloud platforms such as AWS, Azure, or OCI
• Experience migrating data from legacy systems into modern architectures.
• Knowledge and experience with leading AI tools, technologies, and methodologies and how to apply them to business process modernization.
• Excellent analytical, problem-solving, and communication skills.

Preferred Qualifications

• Experience supporting application modernization or digital transformation initiatives.
• Familiarity with microservices-based architectures and service-oriented data flows.
• Experience working with CI/CD pipelines and DevOps tooling for data workflows.
• Knowledge of data governance frameworks and tools (Collibra, Purview, etc.).
• Understanding of security best practices, encryption, identity/access management, and regulatory compliance requirements.