Cleared Hybrid Data Engineer (5418)
$103,000–$171,800 year
On-siteHanover, Maryland, United States
Job Summary
Design, construct, and maintain highly scalable data management systems and robust ELT/ETL pipelines across cloud and on-prem environments. Build infrastructure for optimal data extraction, transformation, and loading using cloud technologies, while implementing monitoring systems to ensure data integrity, quality, and security. Prepare and optimize data for AI/ML models, semantic search, and mission applications, collaborating with analysts and engineers to deliver production-ready datasets. Automate ingestion and transformation processes to optimize performance and cost, troubleshooting pipeline issues as they arise. This role supports priority national security initiatives for the DoD and highly assured solutions for healthcare, requiring a Secret or higher security clearance.
Required Qualifications
- Bachelor's degree in Computer Science, Information Technology, Data Engineering
- 4+ years of progressive professional experience in a data engineering or backend software engineering role
- Security clearance required (Secret or higher)
- Strong proficiency in Python, SQL, Java
- Experience with cloud data warehouses such as Snowflake and AWS Redshift
- Familiarity with distributed computing tools like Spark, Databricks, and Kafka
- Experience with Azure Data Factory, AWS Glue, or similar data integration platforms
- Experience with workflow management tools like Apache Airflow
- Hands-on experience with AWS, GCP, or Azure cloud environments
- Familiarity with multi-cloud data ecosystem patterns
- Experience integrating structured and unstructured data sources
- Knowledge of schema design, data modeling, and cloud-based storage patterns
Desired Qualifications
- Experience supporting AI/ML pipelines, vectorization, or embedding generation
- Experience with data governance, access controls, or sensitive data protection
- Exposure to DevOps/CI-CD patterns for data workflows
- MuleSoft implementation experience
- Experience with real-time data streaming and event-driven architectures
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