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Shield AI is a venture-backed defense-tech company developing intelligent autonomy systems, aircraft, and simulation technologies for military and civilian operations globally. This role leads the Enterprise Data delivery organization, responsible for translating enterprise data strategy into sequenced, achievable delivery plans across platform onboarding, source integration, data-product delivery, semantic enablement, and governance.
You will manage and develop a team of Data Engineers, Analytics Engineers, Domain Enablement Engineers, and Data Governance specialists. Key responsibilities include establishing clear delivery operating rhythms for planning, prioritization, capacity management, roadmap tracking, and stakeholder communication. You'll partner with business leaders and domain stakeholders to shape intake, clarify outcomes, assess readiness, and prioritize use cases while balancing near-term business value with durable, governed data foundations.
You'll coordinate delivery across multiple technical functions, resolve dependencies, and escalate decisions requiring platform, architecture, security, or executive direction. You'll ensure team outputs meet production-readiness standards including data quality, documentation, ownership, lineage, security, and maintainability. Collaboration is central: you'll work closely with the Sr. Staff Data Engineer on ingestion and transformation patterns, the Staff Analytics Engineer on semantic standards and metric definitions, the Platform/Data Reliability Engineer on reliability and cost management, and the Data Governance Specialist on stewardship and metadata.
You'll hire, coach, develop, and retain high performers; establish role clarity and growth expectations; and define practical measures of delivery health including roadmap progress, throughput, adoption, quality trends, and operational stability. You'll communicate delivery progress, risks, and tradeoffs clearly to business and technology leadership, and continuously improve the team's delivery model as the platform and organization evolve.
REQUIREMENTS:
- 12+ years of experience in data engineering, analytics engineering, BI/data platforms, data architecture, or related technical data disciplines
- 3+ years of experience leading and developing technical teams responsible for data, analytics, data products, or data-platform delivery
- Demonstrated success leading delivery across multiple business domains and balancing competing stakeholder priorities
- Strong understanding of modern data-platform concepts including lakehouse architecture, data pipelines, Bronze/Silver/Gold patterns, dimensional modeling, semantic layers, data quality, metadata, lineage, and governed access
- Ability to assess and challenge technical delivery approaches without being the primary hands-on implementer for every solution
- Experience translating business priorities into outcome-oriented roadmaps, scoped delivery plans, and realistic sequencing decisions
- Experience partnering with business stakeholders, software engineering, cloud/infrastructure, security, governance, and architecture functions
- Strong judgment in ambiguous, fast-moving environments with incomplete information and competing demands
- Strong communication, organizational leadership, and stakeholder-management skills
PREFERRED:
- Hands-on experience with Databricks (Delta Lake, Unity Catalog, Databricks SQL, Workflows, or related lakehouse capabilities)
- Experience building or scaling an enterprise data function, data-product operating model, or multi-domain analytics platform
- Experience leading data delivery for Supply Chain, Manufacturing, Finance, Program Finance, GTM, HR, Engineering, or other complex enterprise domains
- Experience in aerospace, defense, autonomous systems, manufacturing, government, or regulated and security-sensitive environments
- Experience leading platform migrations, modernizations, ERP transformations, or enterprise data operating-model change
- Experience managing distributed, remote, partner, or blended internal/external delivery teams
