below marketmost similar roles pay hereabove market
This role pays more than
51%
of similar roles. Most pay
$147,540–$210,815
— the blue band above.
At the midpoint, this role pays about
$169k
versus about
$179k
for comparable roles.
Based on 240 similar postings.
Employer
About Northrop Grumman
Northrop Grumman is a leading global aerospace and defense technology company providing systems in autonomous systems, cyber, C4ISR, space, strike, and logistics. Industry: Aerospace & Defense
Northrop Grumman currently has
629 open roles
on FindRole.
Listed pay typically runs
$117,500–$176,300
across 314 roles with salary data.
The Defense Systems Sector Strategic Deterrence Systems Division is seeking a Sr Principal Data Scientist to provide technical and delivery leadership for a specific business domain. In this role, you will own the domain data pipeline and data product roadmap, leading a data engineering team to build and sustain trusted data products that support program outcomes and downstream analytics. You will lead solution designs, prioritize backlogs, and ensure pipelines meet non-functional requirements like reliability, security, and observability across unclassified, CUI, and higher-side networks. Key technologies and tools include Apache Spark, Delta Lake, Apache Airflow, Kafka, Postgres, and Databricks. You will also integrate data from systems like DOORS, CAMEO, CPLM, SAP, and Workday while managing complex data-model, process, and schema considerations within a highly regulated engineering environment.
What does a Data Scientist earn?
Median $173200 from 338 postings across 66 companies.
Own the domain data pipeline and data product roadmap and lead the data engineering team in its execution.
Prioritize and sequence the domain backlog for build and sustainment work in collaboration with stakeholders.
Lead domain-level solution design for pipelines and data products using shared frameworks and cross-domain data models.
Ensure pipelines meet non-functional requirements for reliability, performance, security, and observability across various network environments.
Represent domain needs, constraints, and risks in cross-domain and platform planning discussions to influence scope and sequencing.
Provide coaching and technical guidance to domain data engineers and pipeline operations roles to improve technical quality.
Work with stakeholders and downstream analytics teams to manage expectations and communicate roadmap status and risks.
Coordinate with engineering leads on architecture decisions and the management of technical risks affecting the domain.
What we're looking for
Must have a Bachelor's degree with 8+ years of experience, a Master's with 6+ years, or a PhD with 4+ years.
Four additional years of relevant experience may be considered in lieu of a formal degree.
Must be able to obtain and maintain a U.S. Government DoD Secret security clearance and Special Access Program (SAP) approval.
U.S. Citizenship is required.
Must have 3+ years of experience leading technical design and delivery for production data pipelines, data products, or integration capabilities.
Must have 3+ years of experience integrating data from multiple enterprise systems of record across one or more business domains.
Must have demonstrated experience prioritizing build-versus-sustainment work, managing technical risk, and leading solution designs for non-functional requirements.
Must have demonstrated experience mentoring engineers and communicating technical decisions to technical and non-technical stakeholders.
Master's degree or PhD in a STEM discipline (preferred).
3+ years of experience as a technical lead in aerospace, defense, or other highly regulated environments (preferred).
3+ years of experience with Apache Spark, Delta Lake, Apache Airflow, Kafka, Postgres, Databricks, or comparable technologies (preferred).
Experience integrating data from systems such as DOORS, CAMEO, CPLM, SAP, and Workday (preferred).
Experience aligning technical roadmaps with control accounts, earned-value baselines, and program milestones (preferred).
Experience operating data products across unclassified, CUI, or air-gapped environments (preferred).