FDE Data Engineer (Space)

Defense Unicorns; New York (NY); Remote; USD 150,000 - 210,000; Full time

Benefits offered by this job

Conferences travel and lodging

Training reimbursements

Unlimited PTO with federal holidays

Medical/Dental/Vision (company paid)

Health Reimbursement Account

Life insurance & disability

401k with company match

Stock options

Home office setup budget

Paid parental leave

Job summary

Defense Unicorns in the United States seeks a forward-deployed data engineer to deploy, integrate, and operate our data stack in mission-relevant environments. You’ll work shoulder-to-shoulder with mission heroes to run workloads in DoD contexts, standing up a governed data platform and connecting it to legacy systems with modern pipelines.

The role emphasizes collaboration, adaptability, and clear communication with government stakeholders, with mostly remote work and occasional on-site visits

Qualifications

• Experience building data pipelines across storage, ingestion, streaming, governance, and access.
• Experience with data provenance, lineage, and governance.
• Ability to work with government stakeholders and translate technical concepts for non-technical audiences.

Responsibilities

• Deploy and configure UDS Data Capability in the mission hero’s environment.
• Build and support integrations with existing mission systems.
• Operate what you deploy, including outage response and capacity planning.
• Generate accreditation artifacts and support cATO/ISSO processes.
• Contribute field feedback to product and engineering and document runbooks.

Skills

Data engineering

SQL

Airflow

Dagster

Argo Workflows

Kubernetes

Kafka

Apache Iceberg

PostgreSQL

Tools

Apache Iceberg

PostgreSQL

Kafka

Job description

• 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 help take UDS Data Capability from “deployable” to “running in production under classification.” You will deploy, integrate, and operate our data stack in the mission hero’s environment alongside senior engineers, 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
• 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
• Deploy and configure UDS Data Capability in the mission hero’s environment. Stand up the UDS Store (Iceberg, Rook/Ceph, pgvector, Postgres), wire up UDS Transit for air-gap data movement, configure UDS Govern policies (Pepr/Lula), and integrate UDS Connect (Strimzi/Kafka) where streaming or legacy connectors are required
• Build and support integrations with existing mission systems. Connect UDS Data Capability to legacy databases, flat-file drops, SOAP/REST endpoints, message buses, existing object storage, and identity providers (Keycloak, mission-side SSO). Prior experience integrating with these types of systems is more relevant than experience building on them
• Contribute to mapping complex data landscapes. Some engagements involve hundreds of interconnected systems of record with overlapping schemas and deeply interdependent data flows. You’ll help trace how data moves across systems and identify dependencies alongside senior engineers and government stakeholders
• Build pipelines that move data through classification boundaries, including ingestion, transformation, catalog registration, model/dataset packaging via Zarf, cross-domain transit, and eventual consistency across DDIL conditions
• Implement data provenance, lineage, and governance practices. Track where data came from, how it transformed, and who can access it
• Operate what you deploy. Day-2 ownership includes capacity, performance, backup/restore (Velero), observability (Vector/Loki), incident response, and upgrade paths. Hand off to the mission hero’s ops team once it’s stable
• Generate accreditation artifacts, including STIG evidence, cATO documentation, FIPS validation notes, and policy mappings. You produce the evidence the mission hero’s ISSM/ISSO needs to run this in IL4/IL5
• Contribute field feedback back to product and engineering. File issues, write postmortems, and surface what’s working and what’s breaking in the mission environment
• Support training and knowledge transfer. Contribute to runbooks, architecture docs, and working sessions that leave the mission hero’s team self-sufficient
• The listed responsibilities are not exhaustive and additional responsibilities may be assigned based on the evolving needs of the organization

Benefits

• Conferences (travel, lodging, and fees)
• Reimbursement for approved trainings/subscriptions
• Unlimited paid time off, with a mandatory 10 days off on top of 11 federal government holidays
• Medical/Dental/Vision (premiums are 100% company paid)
• Health reimbursement account
• Life insurance & disability insurance
• 401k with employer contribution (regardless of employee contribution)
• Company stock options
• Home office setup budget
• Paid parental leave

You should be comfortable building independently against defined problems and growing into more ambiguous, complex engagements over time

You are a data engineer who can build across the breadth of a data platform (storage, ingestion, streaming, governance, and access) and deliver working solutions in constrained, mission-critical environments

We are seeking a dynamic individual who is able to adapt and take on new responsibilities as they arise

Pipelines & orchestration. Airflow, Dagster, Argo Workflows, or similar. Comfort building, scheduling, monitoring, and recovering production data pipelines

Data warehousing. Open-source data warehousing platform experience. These environments do not support proprietary platforms, so you need to be comfortable building without them

Streaming & integration. Experience with stream processing infrastructure (Kafka, Redpanda, Flink, or equivalent) and bridging data from heterogeneous sources into modern pipelines

Unstructured data at scale. Experience storing and querying large unstructured datasets using data lake architectures. Spark experience preferred

Open-source orientation. You are comfortable building on open-source tooling and contributing back to it

Data modeling & SQL. Fluent in SQL. Comfortable designing schemas for both analytical and operational workloads

Comfort with periodic on-site work, sometimes for days at a stretch, and equal comfort working remotely

Comfort working directly with mission heroes and government stakeholders. Clear communication with both technical and non-technical audiences

Self-direction. You will encounter environments and problems that are not yet documented and will need to work through them independently

Bias toward delivery. Preference for shipping a working integration over perfecting a design that hasn’t met a real workload

U.S. citizenship and the ability to obtain and maintain a DoD security clearance. Clearance sponsorship available for the right candidate

You do not need to meet every preferred qualification. You do need to be credible across the core data engineering requirements

DoD or defense program experience

Data provenance, lineage, and governance. Experience with lineage tracking, data catalogs, provenance systems, or governance frameworks. Depth here will be weighted heavily

Active Secret clearance (or higher)

Change Data Capture: Debezium or similar CDC patterns

Lakehouse & storage: Apache Iceberg (or Delta/Hudi), object storage (Ceph/S3-compatible), Postgres (including extensions like pgvector), columnar/OLAP engines (Trino, DuckDB, ClickHouse, Spark SQL)

Governance, catalog & access: REST catalogs (Iceberg REST, Polaris/Gravitino/Nessie family), ABAC/RBAC patterns, OIDC/OAuth, lineage and audit

Linux fundamentals, container runtime behavior, networking, TLS, secrets management

Kubernetes awareness. Deep K8s expertise is not required; general familiarity with deployments, operators, and how applications run on Kubernetes is valuable

IaC (Terraform, Pulumi, or similar) and GitOps patterns (Flux, ArgoCD)

Familiarity with the CNCF ecosystem, including the distinction between foundation projects and single-vendor projects

AI/ML awareness. General understanding of how data infrastructure supports model training, versioning, provenance, and AI operations

Familiarity with Air Force or Space Force systems of record (e.g., MILPDS, ARMS) and how data flows between them