Sr. Manager, Enterprise Data

The AES Group•San Diego, CA

1d•Remote

About The Position

The Senior Manager, Enterprise Data will lead delivery of governed, scalable, business-aligned data products across multiple enterprise domains. The role translates enterprise data strategy into actionable roadmaps, builds high-performing technical teams, and ensures business stakeholders can access reliable, secure, reusable data assets. The position oversees Data Engineering, Analytics Engineering, Domain Enablement, and Data Governance, partnering with senior technology and business leaders to advance platform adoption and operational excellence. The role provides technical oversight of modern data platforms and enterprise architecture alignment while managing delivery across multiple workstreams. It balances immediate business needs with long-term platform scalability, governance, and maintainability. The successful candidate combines modern data platform expertise with people leadership, strategic execution, and the ability to navigate complex stakeholder priorities.

Requirements

12+ years of experience in Data Engineering, Analytics Engineering, Business Intelligence, Data Architecture, enterprise data platforms, or related technical disciplines.
3+ years of experience leading and developing technical teams responsible for data platforms, analytics, data products, or enterprise data delivery.
Proven ability to manage complex delivery portfolios across multiple business domains while balancing competing priorities and stakeholder expectations.
Strong understanding of modern data architecture, including lakehouse concepts, data pipelines, Bronze/Silver/Gold architecture, dimensional modeling, semantic layers, metadata, lineage, data quality, and governed access.
Hands-on experience with Databricks lakehouse capabilities, including Delta Lake, Unity Catalog, Databricks SQL, and Workflows.
Ability to evaluate technical approaches, identify risks, challenge assumptions, and guide sound engineering decisions without being the primary implementer for every solution.
Demonstrated experience translating business objectives into outcome-oriented roadmaps, well-defined initiatives, and achievable delivery plans.
Experience collaborating across business functions, software engineering, cloud infrastructure, security, governance, and enterprise architecture.
Strong organizational leadership, decision-making, problem-solving, and prioritization skills in complex and fast-paced environments.
Excellent communication, team-development, and executive stakeholder-management capabilities.

Nice To Haves

Experience establishing or scaling an enterprise data organization, data-product operating model, or multi-domain analytics platform.
Experience supporting enterprise functions such as Supply Chain, Manufacturing, Finance, Program Finance, Go-to-Market, Human Resources, or Engineering.
Background in aerospace, defense, autonomous systems, manufacturing, government, or other regulated and security-sensitive industries.
Experience leading data-platform migrations, modernization programs, ERP transformations, or enterprise operating-model changes.
Experience managing distributed teams, remote delivery organizations, external partners, or blended internal and external resources.

Responsibilities

Translate enterprise data strategy and business objectives into actionable roadmaps, prioritized initiatives, and measurable delivery outcomes.
Lead a multidisciplinary organization spanning Data Engineering, Analytics Engineering, Domain Enablement, and Data Governance.
Establish delivery practices for planning, prioritization, capacity management, dependency tracking, risk escalation, and stakeholder communication.
Oversee data-platform onboarding, source-system integration, data-product development, semantic enablement, and governance initiatives.
Partner with business stakeholders to evaluate use cases, clarify requirements, assess readiness, and establish realistic delivery commitments.
Balance short-term business priorities with long-term investments in reusable, governed, and maintainable data foundations.
Guide technical delivery so data solutions are secure, scalable, reliable, production-ready, and aligned with enterprise architecture standards.
Provide technical oversight of Databricks lakehouse implementations, including Delta Lake, Unity Catalog, Databricks SQL, and Workflows.
Review technical approaches, implementation plans, risks, and architectural tradeoffs; challenge unnecessary duplication and unsustainable operational practices.
Collaborate with engineering and platform teams to standardize data ingestion, transformation, deployment, observability, and reliability practices.
Ensure enterprise data products incorporate data quality controls, documentation, ownership, metadata, lineage, access controls, and appropriate governance approvals.
Promote consistent semantic standards, metric definitions, dimensional models, and criteria for promoting curated data into Gold-layer assets.
Partner with governance and security teams to embed data stewardship, classification, compliance, and access-management requirements throughout the delivery lifecycle.
Hire, coach, mentor, and retain high-performing technical professionals while establishing responsibilities, performance expectations, and career-development pathways.
Partner with senior data and enterprise architecture leaders to shape operating models, investment priorities, and cross-functional delivery strategies.
Coordinate with business teams, software engineering, cloud infrastructure, cybersecurity, architecture, and governance stakeholders to resolve dependencies and delivery blockers.
Communicate delivery progress, risks, resource needs, and strategic tradeoffs to business and technology leadership.
Define and monitor performance metrics, including roadmap execution, delivery throughput, domain onboarding time, platform adoption, data quality, operational stability, and unresolved dependencies.
Continuously improve delivery processes, team effectiveness, and platform maturity as business needs and organizational capabilities evolve.