[![Image]() Meet Jobicy Copilot — free AI autofill for job applications + remote job alerts ›](#) [All remote jobs](https://jobicy.com/jobs.md)Open role[![Defense Unicorns logo](https://jobicy.com/data/server-nyc0409/galaxy/mercury/2025/06/44a44784-221-1.png)](https://jobicy.com/company/defense-unicorns.md)Remote opportunity at[Defense Unicorns](https://jobicy.com/company/defense-unicorns.md) # Data Engineer (FedD024) Review the role, location requirements, compensation details, and application process before deciding whether this opportunity fits your next career move. [Apply for this job](#job-application)[View company](https://jobicy.com/company/defense-unicorns.md)Share19 Sep 2026Published46Listing views1Application actions19 Oct 2026Apply before Opportunity details ## About this role. AI SummaryThis senior Data Engineer role builds and operates secure, scalable data workflows, pipelines, databases, and exchange services across AWS and on-premises environments. The work centers on Kubernetes-based streaming platforms such as Kafka, Redpanda, and Kinesis, with infrastructure automation through Terraform and strong configuration, security, and performance practices. The engineer will partner with platform and cybersecurity specialists to protect sensitive data and meet DoD and industry compliance requirements. Candidates need at least five years of production data-engineering experience, U.S. citizenship, and the ability to obtain and retain a Secret-level DoD clearance. ## Role DNA A quick view of the complexity, pace, ownership and collaboration implied by the job description. ### Job Complexity 5/5EasyHard ### Pace & Pressure 4/5RelaxedFast-paced ### Autonomy Level 4/5GuidedFull ownership ### Communication Load 4/5IndependentCollaborative AI insightThe role combines advanced data engineering, Kubernetes operations, cloud infrastructure, streaming systems, security, and regulated defense requirements. It also requires independently designing reliable production systems while collaborating across platform and cybersecurity teams. ## Salary analysis Estimated compensation compared with the broader US market for similar roles. Estimated job medianHighly competitive$175,000US market range$135k–$210k0$231k AI insightThe disclosed annual compensation range is $148,750–$201,250 USD, with a midpoint of $175,000. This is competitive for a U.S.-remote senior data engineer with Kubernetes, streaming-platform, AWS, infrastructure-as-code, and defense-security-clearance requirements; the broader estimated U.S. market range is $135,000–$210,000 annually. ## Core skills Skills and capabilities most closely associated with this opportunity. [Data Engineering](https://jobicy.com/jobs?search_keywords=Data%20Engineering.md)[ETL/ELT](https://jobicy.com/jobs?search_keywords=ETLELT.md)[Data Pipelines](https://jobicy.com/jobs?search_keywords=Data%20Pipelines.md)[Apache Kafka](https://jobicy.com/jobs?search_keywords=Apache%20Kafka.md)[Redpanda](https://jobicy.com/jobs?search_keywords=Redpanda.md)[Kubernetes](https://jobicy.com/jobs?search_keywords=Kubernetes.md)[AWS](https://jobicy.com/jobs?search_keywords=AWS.md)[Terraform](https://jobicy.com/jobs?search_keywords=Terraform.md)[Docker](https://jobicy.com/jobs?search_keywords=Docker.md)[Cloud Security](https://jobicy.com/jobs?search_keywords=Cloud%20Security.md) Sample interview questionsHow would you design a secure, scalable data pipeline that moves sensitive data between on-premises systems and AWS?I would begin with data classification, interface contracts, throughput and latency requirements, and applicable compliance controls. I would use encrypted transport and storage, least-privilege IAM, network segmentation, managed secrets, audit logging, and schema validation, then implement resilient ingestion and processing with retries, dead-letter queues, idempotency, and monitoring. I would also document recovery objectives and regularly test backup, restoration, and failure scenarios. Describe your approach to operating Kafka or Redpanda on Kubernetes. I use declarative configuration and an operator or Helm-based deployment model to standardize broker, topic, ACL, and observability configuration. I plan persistent storage, replication factors, partitioning, resource limits, pod disruption budgets, secure authentication and encryption, and capacity thresholds. Operationally, I monitor consumer lag, broker health, throughput, disk usage, and replication health, while validating upgrade and disaster-recovery procedures in nonproduction environments. What practices do you use to make production data pipelines reliable and maintainable? I design pipelines as modular, version-controlled components with clear ownership, data contracts, automated tests, and infrastructure-as-code. I add data-quality checks for freshness, completeness, validity, and schema drift, plus alerting tied to defined service-level objectives. For maintainability, I provide runbooks, lineage documentation, dashboards, and controlled deployment and rollback processes. How would you use Terraform to improve consistency and security in AWS and Kubernetes infrastructure? I would define reusable modules for foundational components such as networking, IAM, encryption, Kubernetes resources, monitoring, and data services. Changes would run through pull requests, policy checks, security scanning, plan review, and controlled CI/CD promotion across environments. I would protect state appropriately, use short-lived credentials where possible, and continuously assess drift and configuration compliance. How do you communicate a complex data-platform risk to nontechnical stakeholders? I translate the issue into mission impact, likelihood, decision options, cost, and timeline rather than leading with implementation details. For example, I might explain that insufficient backup testing could delay recovery of a critical data service, then recommend a tested recovery plan with clear ownership and measurable recovery targets. I confirm the stakeholder's decision, document the accepted risk or remediation plan, and provide concise progress updates. ### EMPLOYER IS A CONTRACTOR FOR THE U.S. GOVERNMENT. THIS POSITION WILL REQUIRE U.S. CITIZENSHIP. ### 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 Travel Expectations/Requirements: 6-10 times per year 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. *Preferred 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 on Kubernetes * Experience in creating data pipelines from scratch with the ability to process data in large volumes and manage data stores * Experience with containerization technologies such as Docker and container orchestration systems like Kubernetes * 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 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. Remote – USA $148,750—$201,250 USD ### Who We Are Defense Unicorns delivers mission value by streamlining software delivery so our customers can focus on the most important challenges. We share a vision of freedom and security for the advancement of progress and innovation. Our commitment to this vision, and to our mission-driven customers, means a commitment to speed, user experience and optionality, without compromising security. Our team is composed of innovators, software engineers, and veterans with decades of experience delivering technology programs across the federal market. ### What We Do We create and deliver secure solutions for continuous software integration and delivery. Defense Unicorns consolidates the best practices for security pipelines, testing, and deployment automation in order to meet the high security requirements valued by mission owners. Our solutions are agnostic by design and we believe that growing a robust ecosystem of secure, cloud-native software solutions can help enterprise customers inside and outside the federal market buy and integrate software more easily. ### Who We Serve Defense Unicorns’ customers are mission-focused leaders across public and private enterprises. We proudly support defense and civil agencies across the U.S. government and we work closely with the creators of leading-edge software solutions to deliver value to the mission-owner by improving the security and consumability of commercial software products. ### What We Work On * Kubernetes * Cloud Environments (AWS/GCP and Azure) * Infrastructure-as-code (like Terraform/Pulumi) * Continuous Delivery and automation tooling * GitOps * Containers * CNCF projects and open source products and packages * Helm/Kustomize-Value Stream Mapping * Building and improving security delivery * Building Kubernetes and cloud native applications ### Benefits Our Unicorns Enjoy ### Health: * Medical/Dental/Vision * Premiums are 100% Company Paid * Health Savings Account * Life Insurance * Disability Insurance ### Financial: * 401k Retirement Plan * Company Stock Options * Home Office Budget ### Leave: * We offer all full-time Unicorns Flexible Time Off (FTO) plus all Federal Holidays, one week for Thanksgiving, and two weeks for Christmas and New Year’s * Paid Parental Leave ### Learning: * Reimbursement for approved trainings/subscriptions * Conferences (travel, lodging, and fees) Don’t have all the preferred experience or qualifications? Studies show that underrepresented groups like women and people of color are less likely to apply to jobs if they don’t meet every requirement listed. At Defense Unicorns, we’re committed to diversity. If you’re enthusiastic about the role but don’t match every criteria, we encourage you to apply. You could be the perfect fit for this or another role! Defense Unicorns is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, disability, sex, sexual orientation, gender identity or expression, age, national origin, veteran status, genetic information, union status and/or beliefs, or any other characteristic protected by federal, state, or local law. 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