Senior FDE Data Engineer (FedD140/FedD148)
AI summary of the role
Senior FDE Data Engineer deploys and operates UDS data stack in DoD mission environments for U.S. government mission heroes.
What you’ll do
- Deploy and harden UDS Data Capability: stand up Store, wire Transit, configure Govern, integrate Connect
- Own integration with legacy databases, endpoints, message buses, object storage, identity providers
- Generate accreditation artifacts: STIG evidence, cATO docs, FIPS notes, policy mappings
What you’ll bring
- U.S. citizenship and ability to obtain/maintain DoD security clearance
- Production experience storing/querying large unstructured datasets using data lake architectures
- Open-source data warehousing platform experience; no proprietary platforms
Technologies
Apache Iceberg · Kafka · Strimzi · Postgres · pgvector · Ceph · Kubernetes · Terraform · Pulumi · Argo Workflows · Airflow · Dagster
About Defense Unicorns
Builds open-source, airgap-native software delivery platforms for DoD mission systems across cloud, on-prem, and tactical-edge environments.
Series A
Source and classification
Internal deployment & tooling · Evidence for this classification:
EMPLOYER IS A CONTRACTOR FOR THE U.S. GOVERNMENT. THIS POSITION WILL REQUIRE U.S. CITIZENSHIP. Role 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 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
More from the job description
EMPLOYER IS A CONTRACTOR FOR THE U.S. GOVERNMENT. THIS POSITION WILL REQUIRE U.S. CITIZENSHIP. Role 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 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, inte [... source excerpt omitted ...] dth of a data platform (storage, ingestion, streaming, governance, and access) and deliver working solutions in constrained, mission-critical environments. About 20% of your time, you'll also invest in the forward-deployed team itself, pairing with junior Data Engineer FDEs on hard problems and helping them develop the technical judgment that only comes from field experience. Responsibilities Deploy and harden 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 [... source excerpt omitted ...] em. Map and navigate complex data landscapes. Some engagements involve hundreds of interconnected systems of record with overlapping schemas and deeply interdependent data flows. You'll need to trace how data moves across systems, identify dependencies, and advise government stakeholders on consolidation and architecture decisions. 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. Establish data provenance, lineage, and governance practices. Track where data came from, how it transformed, and who c
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