Oracle Database Engineer

Peraton•,

7d•$66,000 - $106,000

About The Position

Peraton is seeking a Data Engineer with AI experience to support modernization of two existing business applications. The role assists with evaluating legacy data structures, designing modern data architectures, and enabling reliable, scalable, and secure data flows in the modernization framework using AI tools and methodologies. The ideal candidate has enterprise data engineering, analytics, integration, AI, and cloud modernization experience. The position supports data architecture and modernization, including assessing legacy systems, developing migration and data-quality strategies, establishing data standards, and building scalable data pipelines and integrations. It also analyzes data, translates business needs into data requirements, and creates dashboards and reports to inform modernization decisions. The engineer collaborates with architects, developers, business analysts, and security teams, participates in Agile ceremonies, and contributes to data quality, security, compliance, metadata, lineage, and cataloging. The role also identifies and integrates AI opportunities across the software development lifecycle and DevSecOps, including automation for code analysis, testing, security, and deployment workflows.

Requirements

5 years of experience with a BS/BA, 3 years with an MS/MA, or 0 years with a PhD.
Must be a U.S. citizen.
Must have an active Public Trust.
Experience in data engineering, data analytics, or related roles.
Expert-level SQL proficiency and experience 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, including their application to business process modernization.
Excellent analytical, problem-solving, and communication skills.

Nice To Haves

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

Responsibilities

Assist with designing and implementing modern data architectures, including data models, pipelines, and integration layers.
Assess legacy systems’ data structures, quality, storage mechanisms, and transformation logic.
Define data migration, cleansing, normalization, and reconciliation strategies.
Help establish data standards, naming conventions, and governance practices.
Build and maintain scalable data pipelines for data ingestion, transformation, and distribution.
Implement ETL/ELT solutions using modern data engineering tools and cloud services.
Design APIs, streaming processes, and batch ingestion workflows for system integration.
Ensure data pipelines follow reliability, performance, and security best practices.
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.
Create dashboards, reports, and analytic outputs to support modernization decisions.
Collaborate with architects, system developers, business analysts, and security teams.
Participate in Agile ceremonies and contribute to modernization planning and task prioritization.
Identify data-related risks and issues.
Implement data validation, quality checks, and monitoring across pipelines.
Support metadata management, data lineage, and data cataloging.
Identify and implement opportunities to integrate AI solutions throughout SDLC and DevSecOps processes.
Research AI-driven tools and methodologies to improve automation, efficiency, and accuracy in code analysis, testing, security, and deployment.
Collaborate with development and DevSecOps teams to identify workflows where AI can add value and build or integrate solutions for vulnerability detection, performance optimization, or automated testing.

Benefits

Medical benefits
Dental insurance
Vision insurance
Life insurance
Health savings account
Short- and long-term disability
Employee assistance program (EAP)
Parental leave
401(k)
Paid time off (PTO) for vacation
Company-paid holidays
Depending on the position, employees may be eligible for overtime, shift differential, and a discretionary bonus in addition to base pay.