Sr. Manager, Enterprise Data (R6103)

Shield AI · Remote

  • Senior
  • Full-time
  • $180,000 – $270,000
  • Posted 2026-09-24
  • Confirmed live on 25 September 2026

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Job description

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, semantic layers, data quality, metadata, lineage, and governed access.

• Ability to assess and challenge technical delivery approaches without needing to be 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 qualifications:
• Hands-on experience with Databricks, including Delta Lake, Unity Catalog, Databricks SQL, Workflows, or related lakehouse capabilities.

• Experience building or scaling an enterprise data function, data-product operating model, or mu

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