Sr. Manager, Enterprise Data (R6103)

Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit www.shield.ai. Follow Shield AI on LinkedIn, X, Instagram, and YouTube. 

What you'll do:

Lead and develop the Enterprise Data delivery team, including Data Engineers, Analytics Engineers, Domain Enablement Engineers, and Data Governance specialists. 

Establish clear delivery operating rhythms for planning, prioritization, capacity management, roadmap tracking, dependency management, risk escalation, and stakeholder communication. 

Turn enterprise data strategy and business-domain priorities into sequenced, achievable delivery plans across platform onboarding, source integration, data-product delivery, semantic enablement, and governance. 

Partner with business leaders and domain stakeholders to shape intake, clarify intended outcomes, assess readiness, prioritize use cases, and establish realistic delivery expectations. 

Ensure domain work is appropriately scoped and sequenced, balancing near-term business value with the need for durable, governed, reusable data foundations. 

Coordinate delivery across Data Engineering, Analytics Engineering, Domain Enablement, and Data Governance; resolve dependencies and escalate decisions that require platform, architecture, security, infrastructure, or executive direction. 

Ensure team outputs meet expectations for production readiness, data quality, documentation, ownership, lineage, security, access controls, and maintainability. 

Review delivery plans, technical approaches, risks, and tradeoffs with technical leads; challenge work that creates unnecessary duplication, ungoverned data assets, or unsustainable operational burden. 

Partner with the Sr. Staff Data Engineer to align domain delivery to shared ingestion, transformation, and deployment patterns. 

Partner with the Staff Analytics Engineer to ensure domain assets align to enterprise semantic standards, metric definitions, and Gold-layer promotion expectations. 

Partner with the Platform / Data Reliability Engineer to ensure domain workloads meet platform standards for reliability, observability, cost management, environment promotion, and secure production operation. 

Partner with the Data Governance Specialist to ensure ownership, stewardship, classifications, metadata, lineage, quality expectations, and approvals are incorporated into delivery work. 

Hire, coach, develop, and retain a high-performing data team; establish role clarity, growth expectations, performance feedback, and appropriate technical leadership opportunities. 

Define and monitor practical measures of delivery health, including roadmap progress, throughput, time to enable new domains, adoption, quality trends, operational stability, and unresolved dependencies. 

Communicate delivery progress, material risks, investment needs, and tradeoffs clearly to business and technology leadership. 

Continuously improve the team’s delivery model as the enterprise data platform, domain portfolio, and organizational maturity evolve. 

Required qualifications:

12+ years of experience across 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 …