Mid-Level Systems Engineer - Military veterans preferred

Description

Leidos National Security Sector combines technology-enabled services and mission software capabilities in the areas of cyber, logistics, security operations, and decision analytics to support our defense and intel customers’ mission to defend against evolving threats around the world. Our team’s focus is to ensure our customers have the right tools, technologies, and tactics to keep pace with an ever-evolving security landscape and succeed in their pursuit to protect people and critical assets.

The Intelligence Production Solutions Division (IPSD), part of the Decision Advantage Solutions Business Area is currently seeking a Mid-Level Systems Engineer for the Chinook Program on the Advanced Analyst Augmentation Analytical Cloud Enablement System (4ACES) team. The ideal candidate will have experience with Databricks administration, and solid proficiency in AWS cloud services. This role demands both technical depth and the ability to collaborate with cross-functional teams in a mission-driven environment.

The position combines software development and Commercial Off-The-Shelf (COTS) administration skills, providing on-the-job training (OJT) where you will configure, document and configuration control Databricks resources (e.g., users, workgroups, compute pools, clusters, and related JSON) and AWS resources (e.g., S3 buckets and IdAM policies). You will support automation opportunities (e.g., new reports; administration productivity tools) and service metrics collection and reporting. The position supports multiple Virtual Private Cloud (VPC) Databricks deployments (shards) with 400+ users and data scientists located worldwide. You will collaborate with customers, user workgroups, and vendors to manage the 4ACES platform

Clearance Level Required:

Top Secret clearance with SCI required. Ability to successfully pass a Polygraph exam.

Primary Responsibilities:

• Serve as a Databricks administrator, managing workspace configuration, user roles, cluster performance, and troubleshooting.
• Support AWS infrastructure services including EC2, S3, RDS, IAM, CloudWatch, and Lambda to maintain secure and scalable systems.
• Collaborate with data scientists, developers, and mission analysts to understand system requirements and translate them into effective engineering solutions.
• Develop and maintain infrastructure-as-code (IaC) using tools like CloudFormation or Terraform for consistent and repeatable deployments.
• Participate in Agile development processes, including sprint planning, daily standups, and retrospectives.
• Assist with system integration, security hardening, and operational readiness reviews.
• Produce and maintain system documentation in accordance with NGA standards.

Basic Qualifications:

• US citizenship is required per contract.
• Bachelor’s degree in Computer Science, Information Systems, Engineering, or related field and 4-8 years or prior relevant experience or Master’s with 2-6 years of prior relevant experience.
• Hands-on experience administering and supporting Databricks environments in an enterprise or mission-critical setting.
• Proven experience managing cloud infrastructure in AWS, including services like EC2, RDS, S3, IAM, and networking components.
• Experience developing and testing automation scripts.
• Experience documenting work instructions and configurations.
• Experience with manipulating data with Microsoft Excel, especially transforming and graphing data.
• Experience developing Microsoft PowerPoint presentations, importing images and graphs.
• Familiarity with security and compliance best practices in a classified cloud environment.
• Have or is willing to obtain within 6 months Security+ CE (or similar), required for privileged user (admin) access.
• Experience working within Agile/Scrum teams and using tools like Jira and Confluence.
• Strong problem-solving skills, attention to detail, and ability to work independently or collaboratively in a fast-paced setting.

Preferred Qualifications:

• Experience supporting DoD or IC customers, particularly NGA.
• Familiarity with NGA mission systems and data handling standards.
• Knowledge of containerization (e.g., Docker, ECS, EKS).
• Experience with Python (Pandas, Boto3, PySpark, MLOps), Java or Scala in a data engineering context.
• AWS certification (e.g., AWS Solutions Architect Associate or Professional)
• Familiarity with scripting languages such as Bash, and Bash Scripting.
• Experience with Databricks, Jupyter Notebook, Microsoft Power Query and Power Pivot.
• Strong proficiency in SQL, including advanced performance tuning, query plan analysis, and indexing strategies.
• Experience with transforming data and join/merge with other data sets sharing a common key.
• Software Architectures: Client-Server, Microservices, Model-View-Controller.
• Cloud Exposure:
  • Multi-cloud architectures: AWS, IBM, Google, Azure, and Oracle.
  • Specific AWS Services: Compute (EC2, Lambda), Storage (S3, EBS), Security, Identity & Compliance (IAM, IdAM, KMS), SQS, SNS, and CloudFormation.
  • Certifications such as AWS DevOps Engineer or similar.
• Knowledge of continuous integration and delivery tools: Jenkins, GitLab, and Docker.

At Leidos, we don’t want someone who "fits the mold"—we want someone who melts it down and builds something better. This is a role for the restless, the over-caffeinated, the ones who ask, “what’s next?” before the dust settles on “what’s now.”

If you’re already scheming step 20 while everyone else is still debating step 2… good. You’ll fit right in.

Original Posting:

At Leidos, we don’t want someone who "fits the mold"—we want someone who melts it down and builds something better. This is a role for the restless, the over-caffeinated, the ones who ask, “what’s next?” before the dust settles on “what’s now.”

If you’re already scheming step 20 while everyone else is still debating step 2… good. You’ll fit right in.

Pay Range:

The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.