Deploy and harden UDS Data Capability in the mission hero's environment.
Own the integration with what they already have.
Build pipelines that move data through classification boundaries.
Operate what you deploy — initial day-2 ownership: capacity, performance, backup/restore (Velero).
Generate accreditation artifacts.
Be the voice of the mission hero back to product and engineering.
Train and transfer — leave the mission hero's team self-sufficient.
Grow junior Data Engineer FDEs.

Data engineering breadth
Lakehouse & storage — 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).
Pipelines & orchestration — Airflow, Dagster, Argo Workflows, or similar.
Governance, catalog & access — REST catalogs (Iceberg REST, Polaris/Gravitino/Nessie family), ABAC/RBAC patterns, OIDC/OAuth.
Data modeling & SQL — fluent in SQL; comfortable designing schemas for both analytical and operational workloads.
Kubernetes in production — deployments, operators, CRDs, storage classes, networking.
Linux fundamentals, container runtime behavior, networking, TLS, secrets management.
IaC (Terraform, Pulumi, or similar) and GitOps patterns (Flux, ArgoCD).
Active DoD security clearance required — TS/SCI preferred; minimum active Secret with the ability to obtain TS/SCI.
Comfort being the technical face of Defense Unicorns to a mission hero — listening before prescribing, writing clearly, briefing technical and non-technical stakeholders, and saying "I don't know yet, let me find out" without losing the room.
Self-direction. The mission hero's environment will surprise you, and the answer often isn't in the documentation yet — you'll write it.

Data Engineer – Space

Key skills