Data Engineer; Senior​/Expert

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Engineering Staff Full Time Chantilly, VA, US

Salary Range: $ To $ Annually

Help turn complex data challenges into scalable solutions that support critical mission objectives. Bring your data engineering expertise to NS2 Mission as a Senior/Expert Data Engineer
, supporting our Data Pipeline team in Chantilly, VA
, and driving the development and optimization of reliable, scalable data pipelines and cloud-based platforms.

In this role, you will apply your technical expertise to complex data engineering challenges, developing reliable data processing solutions and optimizing workflows across the data lifecycle. You will collaborate with software engineers, fellow data engineers, and mission stakeholders to translate operational requirements into effective, production-ready solutions. Your experience will help drive technical decisions, improve pipeline performance, and support the continued modernization of mission data capabilities.

This is an opportunity for an experienced engineer to take ownership of critical data engineering initiatives while contributing to the performance, reliability, and evolution of mission-focused systems in an Agile development environment.

• Lead the design, development, enhancement, and maintenance of scalable ETL pipelines and enterprise data workflows.
• Develop and optimize Python-based data processing applications that support complex production requirements.
• Engineer data ingestion, transformation, and integration solutions for structured and unstructured data across multiple platforms.
• Evaluate and improve data pipeline architecture, processing efficiency, data quality, and overall system reliability.
• Design, implement, and sustain cloud-based data engineering solutions within AWS environments.
• Collaborate with cross-functional engineering teams and mission stakeholders to define technical approaches and deliver solutions aligned with evolving mission needs.
• Diagnose and resolve complex pipeline issues, identify root causes, and implement long-term improvements to operational stability.
• Drive the modernization, automation, and optimization of data engineering processes and workflows.
• Support and guide testing, deployment, integration, and sustainment activities across the data platform.
• Establish and promote data engineering best practices related to code quality, scalability, maintainability, and performance.
• Produce and maintain technical documentation covering system design, data workflows, and engineering processes.
• Contribute technical expertise during Agile planning, design reviews, and implementation discussions, helping ensure solutions meet performance and mission requirements.

• Bachelor's degree in Computer Science, Data Engineering, Software Engineering, Information Systems, or a related technical discipline, or an equivalent combination of education and experience.
• Approximately 8-12 years of experience in data engineering, software engineering, or a related technical field, with consideration for candidates whose experience aligns with Senior through Expert-level responsibilities.
• Demonstrated experience across the ETL lifecycle, including the design, development, optimization, and sustainment of data pipelines.
• Strong proficiency in Python for developing and maintaining production-grade data processing applications.
• Hands-on experience designing, implementing, or supporting solutions within AWS environments, including services such as EC2, Lambda, EKS, and S3.
• Proven ability to develop, troubleshoot, and optimize scalable data solutions operating in production environments.
• Strong understanding of data engineering principles, data modeling, performance tuning, and data quality practices.
• Experience collaborating within Agile engineering teams to deliver and sustain complex technical solutions.
• Ability to independently analyze technical challenges, recommend effective solutions, and take ownership of engineering deliverables.

• Experience with workflow orchestration and scheduling tools such as Apache Airflow.
• Experience with containerization and orchestration technologies, including Docker and Kubernetes.
• Familiarity with Infrastructure as Code (IaC) tools such as Terraform.
• Experience with CI/CD pipelines and Dev Ops practices supporting automated testing, deployment, and…