Data Engineer - Mid Forward Deployed Engineer

This is a forward-deployed engineering role. You'll work shoulder-to-shoulder with mission heroes: the users, operators, and program engineers who run real workloads in real DoD environments. You'll be the person who takes UDS Data Capability from "deployable" to "running in production under classification." You will deploy, harden, integrate, and operate our data stack in the mission hero's environment, then carry what you learn back into the product so the next engagement is easier.

The scope of this work varies by engagement. Some programs require standing up a governed data platform to centralize sensor or operational data from known sources, where the problem is well-defined and the priority is building and shipping. Others involve consolidating data across hundreds of interconnected government systems of record with overlapping schemas, deeply interdependent data flows, and significant architectural complexity. You should be equally comfortable executing against a defined data problem and navigating ambiguity in a complex data landscape where the right approach isn't yet clear.

Forward-deployed means aligned with the mission hero, not always on a plane. Most of the work is remote. You'll travel to sites when the engagement calls for it: initial standup, integration work, incident response, training and knowledge transfer. The rest of the time, you'll be on a video call or in a shared chat with that same mission hero. The role is defined by the relationship with the mission hero, not by where you sit.

Responsibilities:

• Designing data workflows, pipelines, and pathways to support ETL/ELT, while ensuring data-quality and exchange of sensitive information across AWS cloud and on-prem environments. 
• Implementing systems engineering principles to ensure the reliability, scalability, and maintainability of data layer systems, including backup and recovery strategies
• Architecting, deploying, and operating data streaming technologies (Kafka, Redpanda, Kinesis, etc ) on Kubernetes with an emphasis on declarative definitions to reduce complexity in day-2 operations
• Working with a platform team to implement best practices for configuration management, security, and performance optimization within Kubernetes and AWS environments
• Working with a platform team to automate infrastructure provisioning, monitoring, and scaling using tools such as Terraform working with cybersecurity SMEs to incorporate best practices and techniques to defend our data layer against potential threats
• Ensuring that our data layer systems are compliant with industry and DoD regulations, standards, and best-practices
• Staying up-to-date with industry trends and emerging technologies related to Kubernetes, containerization, and data engineering

Preferred Locations: Colorado Springs, CO or Florida Space Coast (Cape Canaveral / Cocoa Beach / Melbourne). Remote candidates will be considered, but local presence is strongly preferred.

Travel Expectations: Candidates based in Colorado Springs or the Florida Space Coast can expect on-site presence 1-2 days per week. Remote candidates should expect to travel to the engagement site for approximately one week every 4-6 weeks.

The listed responsibilities are not exhaustive and additional responsibilities may be assigned based on the evolving needs of the organization. We are seeking a dynamic individual who is able to adapt and take on new responsibilities as they arise. 

Required Experience and Qualifications:

• Demonstrated experience (minimum 5 years) in building and maintaining production data pipelines, databases, and data exchange services on Kubernetes Experience in designing, deploying, and operating Kafka / Redpanda data streaming solutions preferably on Kubernetes
• Experience in creating data pipelines from scratch with the ability to process data in large volumes and manage data stores
• Knowledge of systems engineering principles to ensure the reliability, scalability, and maintainability of data layer systems Familiarity with API Security, Container Security, AWS Cloud Security Familiarity with cybersecurity principles and best practices for securing data layer systems
• Excellent problem-solving skills, with the ability to work independently and as part of a team
• Excellent communication skills, with the ability to convey complex ideas to both technical and non-technical team members
•  The selected candidate will be subject to a pre-employment background check ("CBI") and must be able to obtain and maintain a Secret-level DoD security clearance 
• Experience with machine learning and generative AI models

Desired Skills/Experience:

• Experience with containerization technologies such as Docker and container orchestration systems like Kubernetes

Full compensation packages are based on candidate experience. Compensation ranges are established using national benchmarking data and apply across all geographic locations within the United States.