Data Engineer (SME)

Location: Chantilly, VA. 4 days onsite.
Security Clearance: Active TS or higher [Required]
Job Type: Full-Time
Target Salary Range*: $150,000 - $182,000

*This represents the potential salary range for this position depending on education level, years of experience and/or certifications in addition to other position specific requirements which may impact salary

The Data Engineer (SME) provides expert leadership in designing, building, and maintaining data systems supporting advanced analytics and visual intelligence applications. This role develops scalable data pipelines, builds large enterprise relational databases, and ensures secure, efficient data flows across the organization. The SME integrates new data systems with existing platforms and transforms structured and semi-structured data into actionable information.

• Build and maintain data pipelines supporting visual analytics applications and high-performance data processing.
• Transform structured and semi-structured data into usable, actionable information.
• Use open-source, commercial off-the-shelf (COTS), and government off-the-shelf (GOTS) technologies to support analytics and data workflows.

• Design and construct large enterprise relational databases and ensure efficient performance.
• Integrate new data systems with existing enterprise data warehouses.
• Refine system performance to support data processing and analytics needs.

• Develop strategies, standards, and best practices for database operations, programming, and security.

• Collaborate with teams to analyze data needs and improve data quality and usability.

• Bachelor’s degree required.

• Minimum of 10 years of experience.
• Strong experience with relational databases, SQL, and large-scale data design.
• Hands-on experience building pipelines for structured and semi-structured data.
• Experience integrating new systems with enterprise data warehouses.

• Knowledge of data engineering, database development, or related areas.
• Familiarity with analytics, visualization technologies, and high-performance or distributed computing.
• Understanding of secure data practices and zero trust principles.
• Strong communication and problem-solving skills.
• Technical capabilities supporting an in-house, custom-developed data pipeline.

• Kubernetes.
• Terraform.
• GitLab CI/CD.
• JFrog Artifactory.
• AWS cloud services.

• Vue.js.
• Flask.
• Elixir.
• Phoenix LiveView.
• DaisyUI.

• Python.
• Cribl.
• Apache NiFi.
• PostgreSQL.
• Apache Kafka.
• Splunk.
• Custom GOTS applications.
• Complex data parsing and streamlined ingestion.
• Data provenance and end-to-end lineage tracking.
• Schema-aligned ingestion and normalization of diverse structured and unstructured data.

• On-site attendance four days per week.

• Experience with government or multi-enclave data environments.
• Background with data visualization platforms or visual analytics applications.
• Experience with cloud data platforms or hybrid architectures.
• Degree in Data Engineering, Computer Science, or a related field.