Job description

About the Organization Now is a great time to join Redhorse Corporation. We are a solution-driven company delivering data insights and technology solutions to customers with missions critical to U.S. national interests. We’re looking for thoughtful, skilled professionals who thrive as trusted partners building technology-agnostic solutions and want to apply their talents supporting customers with difficult and important mission sets. About the Role Redhorse is transforming how the Department of Defense (DoD) utilizes data and technology. We are seeking a proactive Mid-Level Data Engineer to join our team supporting the Office of the Under Secretary of Defense for Acquisition & Sustainment (OUSD(A&S)). In this role, you will play a key part in advancing data-driven decision-making across the DoD by developing and optimizing robust data pipelines and analytics solutions that support critical national security initiatives. This position offers exceptional visibility and hands-on growth working within enterprise defense data environments. Key Responsibilities Ingest, configure, and transform structured, semi-structured, and unstructured datasets to meet mission partner and stakeholder requirements. Build, automate, and maintain scalable ETL/ELT pipelines supporting DevOps and rapid analytics delivery. Maintain data pipeline operations, monitor environment health, and implement automated performance optimization and cost-reduction practices. Work under general guidance to prototype new data capabilities, evaluate emerging technologies, and deploy end-to-end data solutions. Collaborate with cross-functional technical teams to troubleshoot pipeline bottlenecks, optimize database structures, and implement secure data retrieval methods. Implement and automate DoD Security Technical Implementation Guides (STIGs) across data systems to ensure strict compliance and system security. Required Experience/Clearance US citizenship with an active Department of War (DoW) Top Secret (TS) security clearance and access to Sensitive Compartmented Information (SCI). Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related STEM field with 3+ years of data engineering experience (or Master’s degree with 2+ years of experience). Demonstrated experience developing ETL/ELT pipelines and processing large-scale data using big data frameworks such as Apache Spark. Practical experience working within cloud environments (e.g., AWS, Microsoft Azure, or MilCloud 2.0). Proficiency in core data engineering programming and querying languages (e.g., Python, SQL, or Scala). Familiarity with database architectures, data modeling, and automated configuration management. Familiarity with applying and maintaining DoD Security Technical Implementation Guides (STIGs). Desired Experience We encourage all candidates who meet the basic requirements to apply, even if you do not have any of the following experience: Hands-on experience developing data workflows using Databricks (e.g., Delta Lake, Lakehouse architecture, PySpark). Experience integrating data pipelines with business intelligence and data visualization platforms, particularly Qlik (Qlik Sense or QlikView). Experience working within the DoD Advana Data Environment. Familiarity with deploying and engineering data pipelines across classified networks and multiple security domains. Experience with CI/CD tools and version control systems such as GitLab, Jira, or Jenkins. Active Top Secret (TS) clearance with Sensitive Compartmented Information (SCI) eligibility. The salary range provided for this position represents the anticipated base salary for successful candidates. Actual compensation will be determined based on a variety of factors, including relevant experience, education, certifications, skills, security clearance level, geographic location, market conditions, and internal equity. In addition to base salary, eligible employees may participate in Redhorse's comprehensive benefits programs and may be eligible for performance-based or other incentive compensation, where applicable. Redhorse Corporation is an equal opportunity employer. All qualified applicants will receive consideration for employment and will not be discriminated against on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, disability, or any other protected class. If you are a qualified individual with a disability or a disabled veteran, you may request a reasonable accommodation if you are unable or limited in your ability to access job openings or apply for a job on this site as a result of your disability. You can request reasonable accommodations by contacting Talent Acquisition at Talent-Acquisition@redhorsecorp.com Redhorse Corporation shall, in its discretion, modify or adjust the position to meet Redhorse’s changing needs. This job description is not a contract and may be adjusted as deemed appropriate in Redhorse’s sole discretion.

Requirements

Must-haves

Ingest, configure, and transform structured, semi-structured, and unstructured datasets to meet mission partner and stakeholder requirements.
Build, automate, and maintain scalable ETL/ELT pipelines supporting DevOps and rapid analytics delivery.
Maintain data pipeline operations, monitor environment health, and implement automated performance optimization and cost-reduction practices.
Work under general guidance to prototype new data capabilities, evaluate emerging technologies, and deploy end-to-end data solutions.
Collaborate with cross-functional technical teams to troubleshoot pipeline bottlenecks, optimize database structures, and implement secure data retrieval methods.
Implement and automate DoD Security Technical Implementation Guides (STIGs) across data systems to ensure strict compliance and system security.
Required Experience/Clearance
US citizenship with an active Department of War (DoW) Top Secret (TS) security clearance and access to Sensitive Compartmented Information (SCI).
Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related STEM field with 3+ years of data engineering experience (or Master’s degree with 2+ years of experience).
Demonstrated experience developing ETL/ELT pipelines and processing large-scale data using big data frameworks such as Apache Spark.
Practical experience working within cloud environments (e.g., AWS, Microsoft Azure, or MilCloud 2.0).
Proficiency in core data engineering programming and querying languages (e.g., Python, SQL, or Scala).
Familiarity with database architectures, data modeling, and automated configuration management.
Familiarity with applying and maintaining DoD Security Technical Implementation Guides (STIGs).

Nice-to-haves

We encourage all candidates who meet the basic requirements to apply, even if you do not have any of the following experience:
Hands-on experience developing data workflows using Databricks (e.g., Delta Lake, Lakehouse architecture, PySpark).
Experience integrating data pipelines with business intelligence and data visualization platforms, particularly Qlik (Qlik Sense or QlikView).
Experience working within the DoD Advana Data Environment.
Familiarity with deploying and engineering data pipelines across classified networks and multiple security domains.
Experience with CI/CD tools and version control systems such as GitLab, Jira, or Jenkins.
Active Top Secret (TS) clearance with Sensitive Compartmented Information (SCI) eligibility.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

awsazurepythonsqlci/cdjira

Platform: lever
Effort: quick