Data Architecture, Senior Advisor
Role details
Job location
Tech stack
Job description
This role is the founding owner of a greenfield data and AI platform supporting federal background investigation work. You will design and build the data platform from scratch - owning the architecture end to end, partnering with cloud engineering across the infrastructure boundary, and laying the foundation a growing data science and machine learning team will rely on to deliver state-of-the-art ML and AI capabilities to customers. This is a hands-on role in a high-trust environment where FedRAMP Moderate, NIST 800-171, and CUI handling are first-class design constraints, not afterthoughts. It's also high-ownership work: a modern platform built deliberately on real mission problems. Active clearance preferred; candidates able to obtain one encouraged to apply. Design and stand up the organization's data and AI platform from the ground up - architecture, compute, storage, and the lakehouse foundation.
- Codify the platform as infrastructure-as-code (Terraform) and build the CI/CD pipelines that promote work from development through to the accredited production environment.
- Establish data governance, cataloging, lineage, and fine-grained access control as foundational, not bolted on later.
- Build and own the ingestion, transformation, and pipeline layer that turns raw and synthetic data into governed, analysis-ready data products.
- Design the platform to operate within FedRAMP Moderate, NIST 800-171, and CUI constraints, treating compliance as a first-class architectural requirement.
- Define the artifact promotion process so only signed, validated artifacts cross into the accredited environment.
- Partner with cloud engineering across the infrastructure/security boundary, with clear ownership of the in-platform layer.
- Enable the data science and ML team with the platform capabilities, governed data, and tooling they need to ship models and AI features into the product.
- Own platform reliability, performance, and cost discipline as usage scales.
- Set the engineering standards, patterns, and documentation a growing data team will build on.
Requirements
- U.S. citizenship required.
- Must be able to obtain and maintain a T5/SSBI federally adjudicated clearance; active clearance preferred.
- 8+ years in data engineering / data platform engineering, with demonstrated principal-level ownership.
- Has stood up a data platform or lakehouse from scratch - owning the architecture and build end to end, not operating an inherited one.
- Design of batch (and, where needed, streaming) data pipelines and SQL-based transformations on a lakehouse/Delta foundation, with sound analytical data modeling.
- Infrastructure-as-code (Terraform) and CI/CD for data workloads, including environment promotion from development to production.
- Platform-level data governance: cataloging, lineage, and fine-grained access control.
- Hands-on cloud experience with a major provider (Azure preferred; AWS or GCP considered).
- Strong proficiency in Python and SQL.
- Track record partnering across an infrastructure/security boundary and setting technical standards for other engineers.
- Excellent analytical, troubleshooting, and communication skills.
- Minimum 12 years work experience with BS/BA, * Hands-on Databricks: Unity Catalog, Databricks Asset Bundles, MLflow.
- Experience in regulated or accredited environments: FedRAMP, NIST 800-171, CMMC, CUI handling, or the ATO/RMF process.
- Active security clearance (T5/SSBI or higher).
- Government or defense contracting experience.
- Familiarity with MLOps patterns (model registry, model serving) to support a data science team.
- Cost governance / FinOps discipline for cloud data platforms.
- Spark / PySpark - relevant since the platform is Databricks, though the data volume here does not demand distributed-scale expertise.
Soft Skills
- Ability to translate business needs into performant, well-architected data solutions.
- Strong collaboration across technical and non-technical teams.
- Clear documentation and communication in fast-paced environments.