Automation Engineer
About The Position
Driven by Innovation and built on Trust, rockITdata is a unique SDVOSB services company that partners with leading commercial healthcare/life sciences organizations on cutting edge innovations - think AI, automation and data transformation. We then bring those commercially tested solutions to government entities to deliver predictable, measurable impact for the American taxpayer and consumer. rockITdata is seeking an Automation Engineer to design and develop automated metadata harvesting pipelines using Python and SQL. This role would be responsible for integrating AI/ML capabilities to enable intelligent metadata extraction and implements drift detection systems for ongoing metadata maintenance.
Requirements
- Bachelor's degree in Computer Science, Software Engineering, Data Engineering, or related field
- Minimum 5 years of experience in Python development and SQL
- Experience with AI/ML integration or automation frameworks
- Proficiency with data pipeline tools (Apache Airflow, Prefect, or similar)
- Experience with cloud platforms (AWS, Azure) and their AI/ML services
- Strong understanding of ETL/ELT processes and data integration patterns
- Experience with version control (Git) and CI/CD practices
- Ability to obtain Public Trust clearance
Nice To Haves
- Experience with Amazon Bedrock, Azure OpenAI, or similar generative AI services
- Knowledge of RAG (Retrieval-Augmented Generation) architecture patterns
- Experience with DoD or federal government IT systems
- Familiarity with FedRAMP-compliant cloud environments (GCC-High)
- Experience with SharePoint APIs and Microsoft Graph
- Knowledge of metadata standards and data catalog integrations
Responsibilities
- Design and develop automated metadata harvesting architecture
- Build Python/SQL-based data pipelines for metadata extraction from diverse systems
- Integrate AI tools for intelligent metadata classification and tagging
- Implement Human-in-the-Loop (HITL) validation workflows for AI-assisted harvesting
- Deploy harvesting automation across enterprise systems for scalable metadata capture
- Develop drift detection and alerting mechanisms for metadata change management
- Create and maintain technical documentation for all automation components
- Support empirical testing in sandbox environments for technology evaluations
- Optimize harvesting processes to achieve efficiency gains
- Coordinate with QA teams on automation quality standards
- Troubleshoot and resolve pipeline issues across production environments
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Number of Employees
101-250 employees
