FDE Data Engineer- Space (FedD141/FedD147)

Data engineering breadth

— production experience with Apache Iceberg (or Delta/Hudi), object storage (Ceph/S3-compatible), Postgres (including extensions like pgvector), and at least one columnar/OLAP engine (Trino, DuckDB, ClickHouse, Spark SQL).

Streaming & integration

— Kafka (preferably Strimzi on Kubernetes), Flink or equivalent stream processing, CDC patterns (Debezium), and the ability to bridge legacy systems (Oracle, SQL Server, flat files, SOAP) into modern pipelines.

Pipelines & orchestration

— Airflow, Dagster, Argo Workflows, or similar; comfort building, scheduling, monitoring, and recovering production data pipelines.

Health:

Medical/Dental/Vision

Premiums are 100% Company Paid

Health Savings Account

Life Insurance

Disability Insurance

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 — and 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.

Forward-deployed means

aligned with the mission hero

You'll travel to sites when the engagement genuinely calls for it — initial standup, in-SCIF integration work, on-the-ground incident response, training and knowledge transfer — and you'll be on a video call or in a shared chat with that same mission hero the rest of the time.

You can take responsibility for the full breadth of a data platform — storage, ingestion, streaming, governance, access, and the Kubernetes machinery underneath all of it — make it work where it has to work, analyze what's running through it, and solve problems in real time for the mission hero.

, not

always on a plane

. Most of the work is remote. You'll travel to sites when the engagement genuinely calls for it — initial standup, in-SCIF integration work, on-the-ground incident response, training and knowledge transfer — and you'll be on a video call or in a shared chat with that same mission hero the rest of the time. The job is being

their

engineer, not living at their desk.

You are a data engineer, a data scientist, and a general solutioner. You can take responsibility for the full breadth of a data platform — storage, ingestion, streaming, governance, access, and the Kubernetes machinery underneath all of it — make it work where it has to work, analyze what's running through it, and solve problems in real time for the mission hero. About 20% of your time, you'll also be what makes Defense Unicorns' forward-deployed team itself better — pairing with junior Data Engineer FDEs on hard problems, helping them develop the technical judgment that only comes from doing hard things, and raising the ceiling on what the team can take on.