DataOps Lead - Enterprise Data Platform & AI Readiness

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 / Data Ops Lead to design, implement, and manage enterprise-scale data platforms and pipelines. In this role, you will lead a team to deliver 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 Data Ops-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 and data management standards and processes, drive interoperability across platforms, and ensure data quality, security, and compliance  will work with multiple engineering teams across the enterprise to host, improve, deliver, and integrate their datasets. You will help 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.

What You’ll Be Doing

Corporate Data Management Platform Development and Operations

• Establish and maintain a corporate data management platform on multiple networks including classified and hybrid environments. This includes identifying requirements, setting priorities, shepherding acquisition of COTS and professional services, locating technical support, addressing issues, facilitating communications, collaborating with management on budgets, and acting as a spokesperson for corporate data management across Aerospace.
• Lead the efforts to integrate enterprise data standards, data security, pipelines, data quality, and best practices for automated data ingestion, transformation, validation, and delivery with end user workflows, applications, and data. Develop and track KPIs and metrics.
• Serve as a principal technical lead coordinating data management activities with cross-functional teams to design and implement scalable, secure, and interoperable data architectures aligned with organizational goals with a focus on AI and modeling & simulation integration.

Team Leadership & Collaboration

• Lead a team of 10 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 Data Ops best practices and work with data stewards across the organization through demonstrations, workshops, and training.
• Support DOD, IC, and Civil Federal govt customer dataops strategy, design, implementation activities leveraging Aerospace implementation, best practices, and lessons learned. Collaborate with other FFRDCs as needed.

Innovation & Continuous Learning

• Research emerging tools, architectures, industry trends and standards. Champion potential opportunities to ensure Aerospace remains at the forefront of data engineering.
• Promote a culture of continuous improvement, knowledge sharing, and innovation in data architecture and operations.

What You Need to be Successful

Minimum Requirements:

• Bachelor’s degree in Computer Science, Data Engineering, Computer Engineering, SW Engineering, Information Systems, or a related field (or equivalent work experience).
• 10+ years of experience in data engineering, data architecture, or data…