Data Engineer (FedD024)

defenseunicorns; United States; Remote; USD 149,000 - 201,000; Full time

Benefits offered by this job

Fully paid medical, dental, and vision

HSA access

Retirement matching

Stock options

Home-office budget

Flexible paid time off

Training and conferences

Job summary

defenseunicorns is seeking a data engineer to design, operate, and secure production data platforms across AWS cloud and on‑premises environments. You will handle data pipelines, streaming systems, Kubernetes operations, and infrastructure automation to support government and defense standards.

The role requires 5+ years building data pipelines and deploying Kafka/Redpanda in Kubernetes, with strong security practices and collaboration with platform and cybersecurity teams. Remote US‑based role.

Qualifications

• At least 5 years building and operating production data pipelines, databases, and data-exchange services on Kubernetes.
• Experience deploying Kafka or Redpanda streaming platforms in Kubernetes environments.
• Ability to create high-volume data pipelines from the ground up and manage related data stores.
• Experience with Docker, Kubernetes, systems engineering, API security, container security, and cloud security.

Responsibilities

• Build data workflows and ETL/ELT pathways with strong data quality controls and secure information exchange.
• Apply systems-engineering practices to improve reliability, scalability, maintainability, backup, and recovery of data-layer services.
• Architect, deploy, and operate Kafka, Redpanda, Kinesis, or comparable streaming tech on Kubernetes using declarative configuration.
• Partner with platform engineers on configuration management, security, performance, and infrastructure provisioning in Kubernetes and AWS.
• Use infrastructure-as-code practices (Terraform) and cybersecurity guidance to protect data systems.
• Ensure data platforms comply with DoD and other government regulations and standards.
• Track developments in Kubernetes, containers, streaming, and data engineering to apply improvements.

Skills

Data pipelines

Kafka/Redpanda

Kubernetes

Docker

Terraform

Cloud security

API security

Problem solving

Stakeholder collaboration

Tools

Kafka/Redpanda

Docker

Kubernetes

Terraform

AWS

Job description

Role overview

Design, operate, and secure data platforms that exchange sensitive information across AWS cloud and on-premises environments. This role covers production data pipelines, streaming systems, Kubernetes operations, infrastructure automation, reliability engineering, and compliance with government and defense standards. It is suited to an experienced data engineer who can work independently, collaborate with platform and cybersecurity specialists, and adapt as mission needs evolve.

Responsibilities

• Build data workflows and ETL/ELT pathways with strong controls for data quality and secure information exchange.
• Apply systems-engineering practices to improve the reliability, scalability, maintainability, backup, and recovery of data-layer services.
• Architect, deploy, and operate Kafka, Redpanda, Kinesis, or comparable streaming technologies on Kubernetes using declarative configuration.
• Partner with platform engineers on configuration management, security, performance tuning, infrastructure provisioning, monitoring, and scaling in Kubernetes and AWS.
• Use infrastructure-as-code practices, including Terraform, and incorporate cybersecurity guidance to protect data systems from threats.
• Ensure data platforms align with applicable industry, Department of Defense, and other government regulations and standards.
• Track relevant developments in Kubernetes, containers, streaming, and data engineering and apply appropriate improvements.

Requirements

• At least 5 years of experience building and operating production data pipelines, databases, and data-exchange services on Kubernetes.
• Experience designing, deploying, and supporting Kafka or Redpanda streaming platforms in Kubernetes environments.
• Ability to create high-volume data pipelines from the ground up and manage the associated data stores.
• Experience with Docker, Kubernetes, systems engineering, API security, container security, and cloud security.
• Strong problem-solving skills, self-direction, and ability to work effectively with technical and non-technical stakeholders.
• U.S. citizenship, successful completion of a pre-employment background investigation, and ability to obtain and maintain a Secret-level Department of Defense clearance.

Nice to have

• Experience with machine learning or generative AI models.

Benefits and work setup

• Remote role within the United States, with expected travel approximately 6–10 times per year.
• Published annual US salary range of $148,750–$201,250, with total compensation based on experience.
• Benefits include fully employer-paid medical, dental, and vision premiums, HSA access, life and disability insurance, retirement matching, stock options, a home-office budget, flexible paid time off, federal holidays, paid parental leave, and support for approved training and conferences.