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 Corporation is seeking a skilled Oracle Database Cloud Developer to design, build, and maintain scalable data pipelines and infrastructure. This role focuses on leveraging cloud platforms and relational databases to support data-driven decision-making across the organization.
Key Responsibilities
Design, develop, and maintain robust ETL/ELT data pipelines
Build and optimize data architectures in cloud environments
Develop and manage relational database systems for performance and reliability
Collaborate with data analysts, data scientists, and software engineers to deliver clean, usable datasets
Ensure data quality, integrity, and governance across systems
Monitor and troubleshoot data workflows and pipeline performance
- Implement best practices for data security and compliance
- Required Qualifications
- Active U.S. Government Top Secret/SCI with CI Polygraph is required.
Bachelor’s degree in Computer Science, Engineering, or related field (or equivalent experience)
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10+ years of experience in database administration, engineering, or similar role
Strong experience with relational databases (e.g., PostgreSQL, MySQL, SQL Server, Oracle)
Proficiency in SQL and database design
Experience with at least one cloud platform (Oracle, AWS, Azure, or Google Cloud)
- Hands-on experience with API Gateways, JSON, and low/code tools (e.g. Oracle APEX)
- Desired Qualifications
- Experience with data migration solutions (e.g., GoldenGate)
Familiarity with spatial technologies (e.g., Oracle Cloud Spatial Studio)
Knowledge of containerization and orchestration (Docker, Kubernetes)
Understanding of data modeling techniques
