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# Sr Principal Data Scientist-19908

- **Company:** Northrop Grumman
- **Location:** Roy, UT, United States
- **Experience:** Expert
- **Salary:** $135,000.0 - $202,600.0
- **Contract:** Permanent contract
- **Skills:** Airflow, Systems Engineering, Data Architecture, Information Engineering, Data Integration, Data Structures, PostgreSQL, Operational Databases, SAP (Applications), Software Engineering, Apache Spark, Data Lakes, Information Technology, Apache Kafka, Data Pipelines, Workday, Databricks
- **Published:** October 6, 2026
- **Apply:** https://www.clearancejobs.com/jobs/9221085/sr-principal-data-scientist-19908

## About the Role

* T04: Bachelor's degree with 8+ years of relevant experience; or a Master's degree with 6+ years; or a PhD with 4+ years. In lieu of a formal degree, 4 additional years of relevant experience may be considered.

 * Must have the ability to obtain and maintain a U.S. Government DoD Secret security clearance, with the ability to obtain and maintain Special Access Program (SAP) approval within a reasonable period of time, as determined by the company to meet its business need.

 * 3+ years leading technical design and delivery as a technical lead, domain lead, or equivalent technical owner for production data pipelines, data products, integration capabilities, or a sustained delivery workstream.

 * 3+ years integrating data from multiple enterprise systems of record and working through data-model, process, schema, or dependency considerations across one or more business domains.

 * Demonstrated experience prioritizing build-versus-sustainment work, sequencing delivery, managing technical risk, and aligning domain delivery with stakeholder needs.

 * Demonstrated experience leading solution design and applying shared platform standards and non-functional requirements for reliability, performance, security, observability, and data quality.

 * Demonstrated experience mentoring engineers and communicating technical decisions, delivery risks, and tradeoffs to technical and non-technical stakeholders.

These qualifications would be nice to have:

 * Master's degree or PhD in Data Science, Data Engineering, Computer Science, Software Engineering, Systems Engineering, Aerospace Engineering, or a related STEM discipline.

 * 3+ years serving as a technical lead for data products, domain pipelines, or delivery work in aerospace, defense, or another highly regulated engineering or manufacturing environment.

 * 3+ years building or operating pipelines using Apache Spark, Delta Lake, Apache Airflow, Kafka, Postgres, Databricks, or comparable technologies.

 * Experience integrating data from systems such as DOORS, CAMEO, CPLM, SAP, and Workday into analytical, operational, or data-platform capabilities, including managing source-schema evolution and integration impacts.

 * Experience aligning technical roadmaps, backlogs, and delivery plans with control accounts, earned-value baselines, program milestones, technical risk, and dependency sequencing.

 * Experience working across two or more business domains-including Systems Engineering, Program Management, or Design & Manufacturing-and contributing to cross-domain data models or integration patterns.

 * Experience operating data products across unclassified, CUI, air-gapped, or otherwise constrained environments.

## Description

* Own the domain data pipeline and data product roadmap and lead the domain data engineering team in executing it, ensuring it aligns with program objectives, control account plans, and cross-domain data architecture.

 * Prioritize and sequence the domain backlog (build and sustain) in collaboration with domain stakeholders, team leadership, and program leadership.

 * Lead domain-level solution design for pipelines and data products, ensuring designs leverage shared capabilities (frameworks, orchestration, observability, data quality) and conform to cross-domain data models.

 * Ensure domain pipelines meet non-functional requirements (reliability, performance, security, observability) and governance standards across the environments they run in (e.g., unclassified, CUI, and higher-side networks), including appropriate instrumentation, monitoring, and incident response practices.

 * Represent domain needs, constraints, and risks in cross-domain and platform planning discussions, influencing sequencing, scope, and technical risk mitigation.

 * Provide coaching and technical guidance to domain data engineers, domain observability, and pipeline ops roles, raising technical quality and consistency across the domain team.

 * Work closely with domain stakeholders and downstream analytics/data science teams to understand business needs, manage expectations, and communicate roadmap, status, and risks.

 * Collaborate with system-of-record owners to align domain pipelines with evolving business processes and data structures.

 * Coordinate with the engineering lead and execution lead on architecture decisions, sequencing of cross-domain work, and management of technical risks affecting the domain.