ETL Developer | SME

Amatriot Group, LLC; Chantilly (VA); On-site; USD 145,000 - 190,000; Full time

Job summary

Amatriot Group, LLC is seeking an ETL Developer (SME) in Chantilly, VA to design, develop, and maintain scalable data integration frameworks and BI solutions that enable cyber investigations.

The role builds ETL pipelines, optimizes database performance, and applies DevSecOps practices across multi-enclave environments, collaborating with data architects, DevOps, and infrastructure teams.

Qualifications

• Minimum 10 years of experience in data engineering or related field.
• Strong Python proficiency and experience with ETL pipelines.
• Knowledge of DevSecOps practices, automation, version control, testing frameworks, and CI/CD workflows.
• Experience with data warehousing concepts, data mappings, and database performance tuning.

Responsibilities

• Design, develop, and maintain scalable ETL pipelines and BI solutions.
• Architect ETL pipelines and data mappings to extract, transform, and load complex datasets.
• Write complex database scripts, stored procedures, triggers, and views; tune performance.
• Apply advanced Python proficiency to data integration and application development; implement CI/CD practices.
• Collaborate with data architects, DevOps teams, and infrastructure specialists across multi-enclave environments.

Skills

Advanced Python

ETL pipelines

Data integration

SQL scripting

DevSecOps

CI/CD workflows

Cloud platforms

Containerization

Job description

Location: Chantilly, VA
Security Clearance: Active TS or higher [Required]
Job Type: Full-Time
Target Salary Range*:$145,000 - $190,000

*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

Position Overview

The ETL Developer (SME) designs, develops, and maintains scalable data integration frameworks and business intelligence solutions that enable cyber professionals to analyze case data and advance investigations. This role builds efficient extract, transform, and load (ETL) pipelines, optimizes database performance, and applies DevSecOps practices to support accurate, reliable data processing. The developer collaborates with data architects, DevOps teams, and infrastructure specialists to support applications across multi-enclave environments and advance enterprise data warehousing practices.

Key Responsibilities

Data Integration and ETL Development

• Design, develop, and maintain scalable data integration frameworks and business intelligence solutions.
• Architect ETL pipelines and data mappings to extract, transform, and load complex datasets.
• Integrate modern data pipeline architectures and search indexing technologies to support enterprise data warehousing and cross-functional system integration.

Database Development and Performance

• Write complex database scripts, stored procedures, triggers, and views.
• Conduct performance tuning to ensure data accuracy, processing efficiency, and system reliability.

Python Development and DevSecOps

• Apply advanced Python proficiency to data integration and application development.
• Implement DevSecOps practices, including automation, version control, testing frameworks, and CI/CD workflows.

Application Support and Infrastructure Integration

• Collaborate with data architects, DevOps teams, and infrastructure specialists to support and maintain applications deployed across multi-enclave environments.
• Integrate containerized environments and cloud platforms into data pipeline and application architectures.

Qualifications

Education

Experience

• Minimum of 10 years of experience.

Skills

• Advanced Python proficiency.
• Ability to develop complex database scripts, stored procedures, triggers, and views.
• Knowledge of ETL pipelines, data mappings, and database performance tuning.
• Knowledge of DevSecOps practices, including automation, version control, testing frameworks, and CI/CD workflows.
• Technical capabilities supporting modern data pipeline architectures, containerized environments, cloud platforms, and search indexing technologies.
• Ability to collaborate across data architecture, DevOps, and infrastructure teams supporting multi-enclave applications.