Sr. Manager, Enterprise Data (R6103)

shieldai; United States; Remote; USD 180,000 - 270,000; Full time

Benefits offered by this job

Equity

Bonus

Benefits

Job summary

ShieldAI in the United States is seeking a senior data leader to deliver enterprise data capabilities on a governed lakehouse platform built on Databricks. You will manage multidisciplinary teams onboarding business domains and delivering reliable data products.

You will partner with platform and architecture functions to ensure delivery rests on secure, scalable foundations, define delivery metrics, and coach a high-performing data team through complex, cross-domain initiatives.

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, or data-platform delivery.
• Demonstrated success leading delivery across multiple business domains and balancing competing stakeholder priorities.
• Strong command 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 evaluate and challenge technical delivery approaches without serving as the primary hands-on implementer for every solution.
• Strong communication, organizational leadership, and stakeholder-management skills, with sound judgment in ambiguous, fast-moving environments.

Responsibilities

• Lead and develop a multidisciplinary enterprise data team spanning Data Engineering, Analytics Engineering, Domain Enablement, and Data Governance specialists.
• Establish delivery operating rhythms covering planning, prioritization, capacity, roadmap tracking, dependency management, risk escalation, and stakeholder communication.
• Translate enterprise data strategy and business-domain priorities into sequenced delivery plans across platform onboarding, source integration, data products, semantic enablement, and governance.
• Partner with senior leadership on operating-model design, investment priorities, executive engagement, and cross-functional alignment, coordinating closely with platform engineering and enterprise architecture functions.
• Define and monitor practical delivery-health metrics including throughput, time to enable new domains, adoption, quality trends, operational stability, and unresolved dependencies.
• Hire, coach, develop, and retain a high-performing data team with clear role expectations, growth paths, and performance feedback.

Skills

Data engineering

Analytics engineering

Data platforms

Data governance

Leadership

Stakeholder management

Communication

Tools

Databricks

Delta Lake

Unity Catalog

Databricks SQL

Job description

Role overview

A senior leadership role accountable for delivering enterprise data capabilities on a governed lakehouse platform built on Databricks. The position manages multidisciplinary data teams that onboard business domains, ship reliable data products, and partner with platform and architecture functions to ensure delivery rests on secure, scalable foundations.

Responsibilities

• Lead and develop a multidisciplinary enterprise data team spanning Data Engineering, Analytics Engineering, Domain Enablement, and Data Governance specialists.
• Establish delivery operating rhythms covering planning, prioritization, capacity, roadmap tracking, dependency management, risk escalation, and stakeholder communication.
• Translate enterprise data strategy and business-domain priorities into sequenced delivery plans across platform onboarding, source integration, data products, semantic enablement, and governance.
• Partner with senior leadership on operating-model design, investment priorities, executive engagement, and cross-functional alignment, coordinating closely with platform engineering and enterprise architecture functions.
• Define and monitor practical delivery-health metrics including throughput, time to enable new domains, adoption, quality trends, operational stability, and unresolved dependencies.
• Hire, coach, develop, and retain a high-performing data team with clear role expectations, growth paths, and performance feedback.

Requirements

• 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, or data-platform delivery.
• Demonstrated success leading delivery across multiple business domains and balancing competing stakeholder priorities.
• Strong command 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 evaluate and challenge technical delivery approaches without serving as the primary hands‑on implementer for every solution.
• Strong communication, organizational leadership, and stakeholder‑management skills, with sound judgment in ambiguous, fast-moving environments.

Nice to have

• Hands‑on experience with Databricks, including Delta Lake, Unity Catalog, Databricks SQL, Workflows, or related lakehouse capabilities.
• Background 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.
• Prior work in aerospace, defense, autonomous systems, manufacturing, government, or other regulated and security-sensitive environments.
• Experience leading platform migrations, ERP transformations, or enterprise data operating-model change, including distributed, remote, partner, or blended internal/external delivery teams.

Benefits and work setup

• Listed pay range of $180,000–$270,000, plus bonus, benefits, and equity for regular full-time employees; compensation varies with skill set, experience, certifications, and work location.
• Offers contingent on a cleared background and possible reference check.
• Certain employee categories are not eligible for benefits; accommodations available for disabilities or special needs.