Data Engineer

CACI•Oklahoma City, OK

About The Position

The Data Engineer designs, builds, and sustains data infrastructure and pipelines that power analytics, reporting, automation, and mission-critical decision-making. The role ensures data is reliably ingested, transformed, governed, and delivered across secure enterprise systems. The Data Engineer partners with software engineers, analysts, data scientists, and business stakeholders to provide high-quality, accessible data that supports operational and strategic outcomes. The position builds and maintains scalable data pipelines, data models, integration frameworks, and storage structures, while monitoring data quality, performance, availability, security, and governance. The role also documents architectures and engineering practices and operates within compliance and information assurance requirements, including in regulated or classified environments.

Requirements

At least 5 years of experience as a DBA, Developer, or in a related field.
Commitment to documentation, process improvement, and high-quality engineering practices.
Understanding of data quality, data lineage, and governance in enterprise environments.
Proficiency in at least one programming language used in data engineering, such as Python or Java.
Proficiency in SQL, data modeling, and ETL/ELT development.
Experience building and maintaining data pipelines, integrations, and workflow orchestration in secure environments.
Strong experience working with large, complex datasets across multiple systems.
Experience with relational database and data warehouse technologies.
Familiarity with cloud platforms such as AWS, Azure, or GCP for data engineering workloads.
Ability to collaborate with cross-functional engineering and analytics teams to resolve technical issues.

Nice To Haves

Bachelor’s or master’s degree in information systems, computer science, or a related field.
Experience supporting DoD, Intelligence Community, or other regulated mission environments.
Excellent attention to detail.
Strong ability to multitask.
Strong communication and collaboration skills.
Ability to troubleshoot complex data issues.

Responsibilities

Assemble large, complex datasets from internal and external environments to meet business requirements.
Build infrastructure for optimal extraction, transformation, and loading of data from various sources using AWS, SQL, and other technologies.
Design, build, and maintain scalable ETL/ELT pipelines for analytical, operational, and AI/ML workloads.
Develop and maintain data models, schemas, and storage structures optimized for performance and usability.
Implement data integration frameworks and APIs to enable secure data movement and interoperability.
Collaborate with software engineers, analysts, and data science teams to support workflows.
Monitor, troubleshoot, and optimize pipelines to ensure high availability, data quality, and adherence to governance requirements.
Document data architectures, processes, and engineering standards, and contribute to continuous improvement within Agile/DevOps environments.
Operate within compliance, security, and information assurance requirements, particularly in regulated or classified environments.