Digital Innovation Division DataOps Lead

The Aerospace Corporation is the trusted partner to the nation’s space programs, solving the hardest problems and providing unmatched technical expertise. As the operator of a federally funded research and development center (FFRDC), we are broadly engaged across all aspects of space— delivering innovative solutions that span satellite, launch, ground, and cyber systems for defense, civil and commercial customers. When you join our team, you’ll be part of a special collection of problem solvers, thought leaders, and innovators. Join us and take your place in space.

The Digital Innovation Division (DID) is accountable for generating and executing integrated strategies, providing governance, and managing internal investments that form the foundation of Aerospace’s digital transformation.

The Digital Innovation Division is seeking an experienced Data Engineering / Data Architecture / DataOps Lead to design, implement, and manage enterprise-scale data platforms and pipelines. In this role, you will oversee the full lifecycle of data engineering and integration—from ingestion and storage, to modeling, governance, and advanced analytics enablement. You will be responsible for establishing a modern DataOps-focused ecosystem that enables teams to reliably build, test, and deploy data solutions that power mission-critical applications.

You will lead efforts to define data architecture standards, drive interoperability across platforms, and ensure data quality, security, and compliance at scale. By enabling efficient, automated, and governed data delivery pipelines, you will ensure Aerospace’s digital initiatives are supported by trusted, high-quality data that can be rapidly transformed into actionable insights.

Work Model: 100% onsite; Chantilly, Colorado Springs, El Segundo, Huntsville.

What You’ll Be Doing

DataOps Platform Development

• Integrate enterprise data standards, pipelines, and best practices for automated data ingestion, transformation, validation, and delivery with end user workflows,  applications, and data.
• Work with cross-functional teams to design and implement scalable, secure, and interoperable data architectures aligned with organizational goals.
• Deploy and extend data platforms across multiple environments, including classified networks, cloud, and hybrid infrastructures.

Data Security

• Establish processes to ensure data quality, lineage, and compliance throughout the data lifecycle (ingest → curate → consume).
• Collaborate with InfoSec and compliance teams to maintain adherence to data governance and regulatory frameworks (e.g., NIST, ISO, FedRAMP).
• Implement metadata management, master data management, and access control policies to safeguard sensitive information in our DataOps Platform.

Partnering & Infrastructure Management

• Collaboration to select, configure, and maintain tools for data pipeline orchestration, real-time streaming, and scalable storage.
• Collaboration to drive adoption of modern cloud-native and integrate data services where appropriate.
• Collaboration to integrate the enterprise data management platform with the AI/ML platform to enable seamless data access, feature engineering, and model training at scale.
• Collaboration to integrate the enterprise data management platform with the COTS and custom developed analytical applications to enable seamless data access, analysis, lineage and reuse.
• Optimize resources to maximize uptime, reliability, and performance of the enterprise data ecosystem.

Governance & Process Improvement

• Develop and track key data metrics and KPIs (e.g., data quality scores, pipeline reliability, data delivery SLAs).
• Integrate DataOps processes with corporate governance standards to ensure transparency, repeatability, and efficiency.
• Establish feedback loops with data consumers to continuously improve performance, trust, and usability of data products.

Team Leadership & Collaboration

• Lead a team of data engineers, data architects, and platform specialists; provide mentorship and career development.
• Leverage Agile methodologies to manage priorities, sprint planning, and cross-team collaboration.
• Promote DataOps best practices and work with data stewards across the organization throug