The Sr. Manager, Enterprise Data is responsible for leading delivery across Shield AI’s Enterprise Data team as the organization enables business domains onto its governed Databricks data platform.
This role manages the engineers and delivery work required to turn enterprise data strategy into usable, reliable data products. The Sr. Manager will establish effective delivery rhythms, guide domain prioritization, manage capacity and dependencies, and ensure that business needs are translated into clear, appropriately scoped work for the Data Engineering, Analytics Engineering, Domain Enablement, and Data Governance functions.
The role requires substantial data and analytics depth to assess delivery approaches, challenge unclear requirements, make appropriate tradeoffs, and ensure that the team produces durable, governed, production-ready outcomes rather than one-off reporting solutions.
The Sr. Manager partners closely with the Sr. Director of Enterprise Data & Architecture on strategy, operating model, investment priorities, executive engagement, and cross-functional alignment. The role partners with Platform Engineering and Enterprise Architecture, which remain direct functions of the Sr. Director, to ensure domain delivery is built on secure, reliable, scalable enterprise foundations.
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 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 another regulated and security-sensitive environment.
- Experience leading platform migrations, modernizations, ERP transformations, or enterprise data operating-model change.
- Experience managing distributed, remote, partner, or blended internal/external delivery teams.
Skills Required
- 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 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.
- 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 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 another regulated and security-sensitive environment.
- Experience leading platform migrations, modernizations, ERP transformations, or enterprise data operating-model change.
- Experience managing distributed, remote, partner, or blended internal/external delivery teams.
What the Team is Saying
Shield AI Compensation & Benefits Highlights
-
Healthcare Strength — Healthcare coverage is described as excellent, with dental/vision and mental‑health support, and ancillary protections like life and disability appearing in benefit summaries. The breadth and perceived affordability of coverage are highlighted as a standout component of the package.
-
Parental & Family Support — Paid parental leave is featured alongside enhanced maternity benefits, fertility and childcare support, and onsite resources such as a Mother’s Room. These elements are positioned as competitive and above the minimal baseline for the company’s stage.
-
Equity Value & Accessibility — Equity is granted to all full‑time hires, with RSUs, double‑trigger tax timing, and tools to model scenarios (e.g., through Carta Tax). Communications also reference a transition from options to RSUs, reinforcing access and maturity of ownership programs.
Shield AI Insights
What We Do
At Shield AI, you won't wait years to see your work reach the field. You'll build hardware and software that operates in the real world right now, in the hands of the people who depend on it. Hivemind, our AI pilot, has been flying since 2018. It has flown more than 30 platforms, including an F-16, and it now sits under a U.S. Air Force production contract for Collaborative Combat Aircraft. When you write code or shape a system here, you contribute to technology with a proven flight record and a clear production future. V-BAT flies intelligence, surveillance, and reconnaissance missions with an operational record that stretches from Ukraine to the Indo-Pacific. It delivers eyes where they matter most, in the most demanding conditions on earth. The teams behind it watch their work get tested where the stakes are real. X-BAT takes its first flight this year. It's an AI-piloted fighter that needs no runway, built to operate where traditional aircraft can't. Join now and you help shape a program at its earliest, most formative stage. That's the kind of ground-floor work that defines a career. Do the most impactful work of your life, on problems that matter. Autonomy at this level asks a lot of you. You'll take on problems in perception, planning, and control that few teams anywhere are equipped to solve. You'll work across disciplines, from aerospace and robotics to machine learning and systems engineering, alongside people who hold themselves to an exacting standard and expect the same from you. Our mission is clear: protect service members and civilians with intelligent systems. That purpose runs through every decision, every design review, and every deployment. It's why the work here carries a weight you can feel. Ready to join our mission? Explore our open roles and find where you fit.
Why Work With Us
Founded in 2015 by a former Navy SEAL, Shield AI builds AI pilots and uncrewed aircraft. Veterans aren't an afterthought here, they're at every level. It's why the work carries weight: AI pilots and uncrewed aircraft flying real missions, from Ukraine to the Indo-Pacific, protecting service members and civilians.
Gallery
%203.jpg)
Shield AI Teams
.jpg)
Shield AI Offices
Hybrid Workspace
Employees engage in a combination of remote and on-site work.
