Data Platform Engineer (Senior)

Location: Chantilly, VA
Security Clearance: Active TS or higher [Required]
Job Type: Full-Time
Target Salary Range*: $135,000 - $150,000

*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 Platform Engineer (Senior) supports advanced visual analytic applications by building and sustaining data pipelines, designing relational data platforms, and enabling high-performance analysis across structured and semi-structured data. This role helps streamline data processing, improve platform performance, strengthen secure data practices, and support scalable enterprise data services.

The position also supports modern platform engineering capabilities across Kubernetes, Infrastructure as Code, CI/CD, cloud services, user interface components, ETL technologies, streaming platforms, and enterprise data integration while contributing to cross-team standards and mentoring junior team members.

• Develop data-processing workflows and analytics for desktop- and web-based visual analytic tools.
• Build and maintain secure data-ingestion pipelines using open-source, COTS, and GOTS technologies.
• Design and optimize enterprise relational databases and establish standards for operations and security.
• Integrate new data systems with existing data warehouses and improve performance and functionality.
• Support large-scale relational data analysis using visualization and high-performance computing.
• Contribute to system optimization, secure posture improvements, and cross-team technical standards.

• Support Kubernetes-based data platform environments.
• Develop and maintain Infrastructure as Code using Terraform.
• Support GitLab CI/CD pipelines for automated build, integration, and deployment.
• Manage software artifacts and dependencies using JFrog Artifactory.
• Support data platform services hosted within AWS cloud environments.

• Develop and support ETL workflows using Python, Cribl, and Apache NiFi.
• Support PostgreSQL database environments.
• Develop and maintain Apache Kafka-based data streaming and integration capabilities.
• Integrate Splunk and custom GOTS applications into enterprise data-processing workflows.
• Perform complex data parsing and streamlined ingestion.
• Support provenance and end-to-end data lineage tracking.
• Perform schema-aligned ingestion and normalization of diverse structured and unstructured data.

• Support user interface and application components using Vue.js, Flask, Elixir, Phoenix LiveView, and DaisyUI.
• Integrate application components with backend data-processing and platform services.

• Mentor junior team members.
• Contribute to data platform standards, engineering practices, and operational improvements.
• Support improvements to data workflows, platform performance, and security.

• Bachelor’s degree. [Required]

• Minimum 8 years of relevant experience. [Required]
• 8+ years of experience in data engineering, database design, or related fields. [Required]
• Experience working with structured and semi-structured data and visualization technologies. [Required]
• Familiarity with high-performance computing and mixed-technology environments. [Required]
• Experience improving data workflows, performance, and security. [Required]

• Strong relational database design skills. [Required]
• Strong SQL skills. [Required]
• Strong ETL/ELT processing skills. [Required]
• Strong analytical, communication, and collaboration skills. [Required]

• Experience supporting federal or secure, multi-enclave environments.
• Background with advanced visualization platforms or high-volume data processing.
• Knowledge of data modeling, data warehousing, and performance tuning.