Delivery Lead - Acquisition & Sustainment

Now is a great time to join Redhorse Corporation. We are a solution-driven company delivering data insights and technology solutions to customers with missions critical to U.S. national interests. We’re looking for thoughtful, skilled professionals who thrive as trusted partners building technology-agnostic solutions and want to apply their talents supporting customers with difficult and important mission sets.

End-to-End Delivery & Execution

• Take ownership of the team's delivery lifecycle, ensuring data products are delivered on time, within scope, and to quality standards.
• Ensure the product backlog is prioritized, refined, and clearly understood by the cross-functional team.
• Track and communicate team metrics (e.g., velocity, sprint burn-down, lead time) to forecast delivery and identify areas for process optimization.
• Proactively identify, escalate, and resolve impediments and blockers that hinder the team’s progress.

Agile Facilitation & Team Leadership

• Guide and coach the team in engineering best practices.
• Foster a collaborative, high-performing team culture rooted in trust, transparency, and continuous learning.
• Protect the team from external distractions and scope creep during active sprints.

Enterprise Stakeholder & Dependency Management

• Act as the primary bridge between the execution team and wider enterprise stakeholders, ensuring clear communication of progress, risks, and release schedules.
• Navigate a highly matrixed enterprise environment to manage complex dependencies with external teams.
• Prepare and deliver executive-level status reports and delivery roadmaps.

Data Product Advocacy & Compliance

• Ensure delivery aligns with enterprise data governance and security standards.
• Possess a strong working understanding of the data product lifecycle (data ingestion, transformation, modeling, and visualization) to effectively communicate with technical team members and validate delivery estimates.
• Facilitate discussions around data quality, testing protocols, and CI/CD pipelines specific to data environments.