Senior Data Engineer (FedD238)

Description

You will embed with a government team and its technology partners on an AI-powered engineering ecosystem that is still taking shape.

The work centers on preparing enterprise data so AI systems, agents, and mission software can find it, trust it, and use it under proper governance.

The scope covers ingestion, transformation, storage, metadata, APIs, search, vector and graph stores, and the point where the data layer meets AI workloads.

Strong candidates are hands-on engineers who can handle the full data lifecycle, know that missing or poorly connected data usually stalls AI work, and are comfortable joining an unfinished architecture, picking up unfamiliar systems quickly, and working directly with commercial vendors on data quality, lineage, access, performance, and security.

Reporting and dashboard work is not the focus. The aim is to build data foundations and repeatable patterns so AI and agent capabilities can use trusted data and move from prototype to production in secure and classified settings.

The company builds secure tooling that automates software delivery for federal and civil agencies and works with vendors creating cloud-native products.

Responsibilities

• Build and maintain dependable pipelines that ingest, transform, check, and deliver data to AI models, agents, and mission applications.
• Bring structured and unstructured sources into enterprise data services across relational, document, vector, and graph systems.
• Partner with AI and agent engineers so data can be found and used for RAG, semantic search, model context, and agent tool workflows.
• Create reusable ingestion and transformation patterns using Python, SQL, APIs, event-driven designs, and workflow orchestration tools.
• Set up data quality checks, validation, provenance, lineage, and metadata so users and AI systems can rely on what they receive.
• Design access paths that enforce identity, authorization, classification, and security boundaries without adding needless friction for developers and mission users.
• Work with platform engineers to run data services on Kubernetes and OpenShift and connect them to CI/CD and GitOps workflows.
• Help fold data capabilities such as relational stores, JSON and document data, vector search, graph data, analytics, and RAG services into the wider platform design.
• Trace data problems end to end across source systems, pipelines, storage, APIs, identity, networking, platform services, and AI applications.
• Work directly with government engineers and commercial partners to clear data dependencies and unblock delivery.
• Write documentation, data contracts, schemas, architecture decision records, runbooks, and operating standards so good patterns repeat across environments.
• Spot recurring data engineering problems that can be standardized, automated, or packaged as products rather than solved by hand each time.
• Keep working in an ambiguous setting where sources, architecture, security rules, and mission priorities keep changing.

Requirements

• Active TS/SCI clearance.
• 7+ years in data engineering, data platform engineering, or a closely related field.
• Strong SQL and Python skills for data processing, automation, and integration.
• Hands-on experience building and running production pipelines and ETL/ELT workflows.
• Experience with relational databases and modern storage for structured and unstructured data.
• Experience integrating data through REST APIs, message or event systems, or other distributed patterns.
• Working knowledge of data modeling, schema design, data quality, lineage, metadata, and governance.
• Experience running cloud-native or containerized systems alongside Kubernetes or platform teams.
• Ability to troubleshoot data problems across infrastructure, applications, APIs, storage, networking, and access controls.
• Ability to work alone, learn new technologies fast, and turn unclear mission needs into working data solutions.
• Preferred, though not required: GEOINT experience.
• Preferred: experience supporting AI and ML work such as RAG, embeddings, vector search, model context, or agentic applications.
• Preferred: experience with vector, graph, document, or knowledge graph databases, or semantic search tools.
• Preferred: experience with Oracle or similar enterprise platforms covering relational, JSON, vector, graph, and analytics workloads.
• Preferred: experience designing data products or platforms for high-scale, low-latency, or mission-critical use.
• Preferred: experience with orchestration tools such as Airflow, Dagster, Argo Workflows, or similar.
• Preferred: experience with streaming platforms such as Kafka, Redpanda, NATS, or similar.
• Preferred: experience deploying data services with Kubernetes, Helm, GitOps, infrastructure as code, and automated CI/CD.
• Preferred: experience with data and AI systems in Secret or TS/SCI settings across multiple security domains.
• Preferred: experience with disconnected or air-gapped environments and moving data, metadata, and software across security boundaries.
• Preferred: familiarity with NIST 800-53, RMF/ATO, zero-trust architectures, and data security and compliance practices.
• Preferred: experience with enterprise search, RAG pipelines, data catalogs, data contracts, or knowledge graph architectures.
• Preferred: familiarity with UDS, Zarf, Pepr, Iron Bank, or similar secure software delivery tools.
• Preferred: experience on mixed teams of government engineers, FDEs, OEM professional services teams, and several technology vendors.
• Preferred: track record of turning a fragmented or difficult data environment into a dependable, reusable base for mission applications and AI.

Conditions

Remote within the USA.

Be local to the National Capital Region and able to support onsite work at a government facility in Springfield, VA as mission needs increase.

Pay range is $148,750 - $201,250 USD.

Pay depends on experience. Ranges are set from national benchmarking data and apply in all US locations.

Candidates who do not meet every preferred qualification are still encouraged to apply.

Benefits

• Medical, dental, and vision coverage with 100% of premiums paid by the company.
• Health savings account.
• Life insurance and disability insurance.
• 401k retirement plan.
• Company stock options.
• Home office budget.
• Flexible time off (FTO), all federal holidays, one week for Thanksgiving, and two weeks for Christmas and New Year's.
• Paid parental leave.
• Reimbursement for approved trainings and subscriptions.
• Conferences, with travel, lodging, and fees covered.