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Confidential · 15 hours ago

Head of Enterprise Data & Architecture

Dallas, TX

Full-time

Onsite

Director/Executive

20+ years exp

Confidential is seeking a Head of Enterprise Data & Architecture who will be responsible for architecting the company’s future-state data foundation. This role involves owning the enterprise data strategy, designing a unified data architecture, and establishing governance frameworks to enable automation and advanced analytics across the organization.

Marketing & Advertising

Hiring Manager

Matt Stella

Responsibilities

Define and execute the future-state enterprise data strategy, focused on automation, interoperability, machine-readable structures, and AI enablement

Design and own the enterprise data model across all systems, ensuring it is optimized for real-time insights, predictive analytics, and scalable automation

Architect cloud-first, modular, intelligent data platforms that support high-volume ingestion, transformation, and consumption across planning, reporting, and operational workflows

Establish forward-looking data standards that ensure system designs are AI-ready, lineage-aware, and automation-friendly

Rebuild the chart of accounts, legal entity hierarchy, and financial dimensions with a forward-looking design that supports global expansion, multi-scenario modeling, automation, and self-service analytics

Define a unified global capability model across Finance, HR, Procurement, and Operations, ensuring cross-system constructs are consistent, reusable, and machine-actionable

Develop scalable transformation rules, metadata models, and canonical structures to streamline future integrations and new-system adoption

Architect end-to-end integrations that support automated, intelligent data flow across core platforms, including: Workday → D365 → OneStream → Power BI

Implement event-driven, API-led, and streaming integration patterns that improve timeliness, reduce latency, and enable autonomous reconciliation

Establish global mapping rules, validation logic, and lineage requirements enforced through automated controls and monitoring

Ensure integration frameworks support predictive exception handling, ML-driven anomaly detection, and automated quality remediation

Own the enterprise data governance framework, ensuring it evolves to support advanced analytics, GenAI, agentic workflows, and automated decisioning

Implement automated data quality checks, lineage intelligence, metadata-driven orchestration, and continuous monitoring

Establish enterprise-wide rules for access, classification, privacy, and usage to ensure data is trustworthy, secured, and compliant for both human and AI consumption

Drive enterprise-wide adoption of stewardship practices supported by intelligent tooling

Lead the uplift of existing systems by remediating legacy design flaws, removing structural inconsistencies, and eliminating manual workarounds

Replace brittle processes with automated pipelines, governed integrations, and reusable architectural patterns

Create a modernization blueprint that accelerates autonomy, resilience, and scalability across the entire data and systems state

Ensure future implementations adopt best-in-class design principles aligned to automation, AI, and low- or no-touch operations

Partner with Finance, HR, Operations, Technology, and business leaders to develop a unified, automation-centric vision for data and architecture

Influence executive decision-making by articulating a future-state architecture that reduces operational friction and unlocks AI-enabled insights

Champion a culture of innovative thinking, intelligent automation, continuous optimization, and data-driven decisioning

Coach and develop architects and technical leaders to adopt modern architectural methods, metadata-driven design, and AI-first thinking

Define KPIs that measure progress toward an autonomous and AI-ready enterprise, reducing manual effort, increasing reliability, and accelerating insights

Drive material improvements in financial close speed, reporting accuracy, mapping precision, and system reliability through automation and re-architecture

Enable predictive analytics, proactive exception detection, and AI-driven scenario modeling through well-designed data structures and intelligent workflows

Deliver a unified architectural foundation that significantly enhances productivity, reduces cost, and improves operational agility

Qualification

Enterprise data architectureAI/ML enablementCloud-based integrationData modelingWorkdayD365OneStreamPower BIMetadata managementExecutive influenceCommunication skills

Required

20+ years of experience in enterprise data architecture, integration, or corporate systems architecture, preferably in global financial or information-driven organizations

Proven ability to design future-state data architectures, automate workflows, and enable AI/ML across core enterprise functions

Deep expertise in enterprise financial structures, data modeling, metadata management, lineage design, master data, and semantic layer development

Significant experience with Workday, D365, OneStream, Power BI, and cloud-based integration frameworks

Demonstrated success modernizing legacy systems, redesigning foundational structures, and implementing automation-first architectures

Strong capability in cloud-native engineering, API-led integration, event-driven architecture, and metadata-driven automation

Outstanding communication and executive influence skills with the ability to translate complex architectural vision into business outcomes

Company

Confidential

Silicon Valley, California US, US

51-200 employees

Funding

Current Stage

Growth Stage

Leadership Team

Roshan Syed

Global Talent Partner

Company data provided by crunchbase