Sr Director, Enterprise Data and Architecture
Shield AI
IT
Remote
USD 214k-322k / year + Equity
The Sr Director of Enterprise Data and Architecture leads the strategy, execution, and governance of enterprise data, integrations, and Enterprise Systems Architecture across the organization. This role is responsible for defining and delivering modern data platformsand enterprise architecture that enables trusted, governed, and accessible data across ERP, CRM, HRIS, Manufacturing, Finance, and other core systems.
As the owner of corporate data strategy and the enterprise data lakehouse, this leader drives the design and build of scalable data platforms, integration patterns, and architectural standards that support analytics, AI, operational reporting, and digital products. The role ensures that data and technology decisions align with business strategy, regulatory obligations, and security requirements.
The ideal candidate brings deep expertise in enterprise data architecture, data engineering, and integrations, along with a proven ability to lead cross-functional programs, mature data governance, and build high-performing architecture and data engineering teams.
What You'll Do:
Enterprise Data Strategy & Governance
Develop and own the enterprise data strategy and roadmap, aligning data capabilities with corporate objectives, analytics needs, and digital transformation priorities.
Define the vision, operating model, and maturity path for data as a product, including policies for data ownership, stewardship, quality, security, and lifecycle management.
Establish and chair cross-functional data governance forums that bring together business, IT, security, and compliance stakeholders to prioritize data initiatives and enforce standards.
Set enterprise-wide standards for metadata, master data, and reference data to ensure consistency and interoperability across systems and domains.
Data Lakehouse & Platform Ownership
Own the design, build, and evolution of the corporate data lakehouse, including ingestion pipelines, storage layers, semantic models, and downstream analytics enablement.
Lead data engineering and platform teams in delivering reliable, performant, and cost-efficient data platforms that support BI, advanced analytics, AI/ML, and self-service reporting.
Define architecture patterns for batch and streaming pipelines, ELT/ETL frameworks, and data orchestration, ensuring resilience, observability, and scalability.
Evaluate and select data platform, integration, and analytics technologies; manage vendor relationships and drive adoption of best-in-class tools and practices.
Integrations & Enterprise Systems Architecture
Own the enterprise integration strategy across ERP, CRM, HRIS, Manufacturing, Finance, and other core platforms, including APIs and middleware.
Define end-to-end architecture standards and reference architectures that ensure secure, scalable, and loosely coupled integrations between enterprise applications and the data lakehouse.
Lead architecture reviews for major initiatives, ensuring solution designs adhere to enterprise patterns, leverage reusable components, and maintain long-term sustainability and supportability.
Partner with application owners (ERP, CRM, HRIS, Manufacturing, Finance) to align roadmaps, minimize duplication, and ensure data and integration requirements are built into platform strategies.
Analytics, Insights & Enablement
Collaborate with Finance, Operations, Commercial, and functional analytics teams to prioritize data products and reporting capabilities that drive measurable business outcomes.
Define enterprise reporting and analytics architectures, including canonical models, subject-area data marts, and governed semantic layers for BI tools.
Enable self-service analytics by providing high-quality curated datasets, documentation, and training for business and data users.
Partner with AI/ML and advanced analytics teams to ensure data platforms and architectures support experimentation, model deployment, and responsible AI practices.
Leadership, Operations & Risk Management
Build, mentor, and lead high-performing teams across data architecture, data engineering, and enterprise architecture disciplines.
Define KPIs and OKRs for data platform reliability, data quality, integration performance, delivery velocity, and business value realization; provide regular reporting to executive leadership.
Oversee budgets, vendor contracts, and resourcing for data and integration platforms, ensuring cost-effective scaling and clear ROI.
Partner with Security and Compliance to ensure data and integration architectures meet regulatory, contractual, and organizational risk requirements.
12+ years of experience in enterprise data, analytics, or architecture roles, including 5+ years in senior leadership driving enterprise-scale data or architecture programs.
Proven experience owning data strategy and leading the design and delivery of modern data platforms such as data warehouses, data lakes, and/or lakehouse architectures.
Deep expertise in enterprise data architecture, data modeling, and data integration patterns (e.g., APIs, streaming, ETL/ELT, event-driven architectures).
Demonstrated success implementing and maturing data governance, data quality, and metadata management practices in complex organizations.
Strong background designing integrations and architectures across multiple enterprise platforms (ERP, CRM, HRIS, Finance, Manufacturing, or similar).
Experience leading cross-functional programs with multiple stakeholders, including IT, business functions, security, and external partners.
Excellent executive communication and stakeholder management skills, with a track record of influencing senior leaders and driving alignment on complex technical decisions.
15+ years of progressive experience in data, architecture, or enterprise technology leadership roles.
Hands-on leadership experience with one or more major cloud data platforms or lakehouse technologies (e.g., Snowflake, Databricks, Microsoft Fabric, BigQuery, or equivalent).
Experience architecting data and integration solutions in regulated or security-sensitive industries (e.g., defense, aerospace, healthcare, or financial services).
Background in supporting analytics, AI/ML, or advanced analytics programs on top of enterprise data platforms.
Familiarity with enterprise architecture frameworks and methods (e.g., TOGAF, domain-driven design, data mesh) and their application in modern data and application landscapes.
Bachelor’s degree in Computer Science, Information Systems, Engineering, or related field; advanced degree in a technical or business discipline preferred.
214000 - 322000 USD a year