Job description
The Global Data Architect role is a strategic leadership role responsible for defining and guiding global data architecture across Global Services and Member Firm environments. This role enables scalable analytics, AI, and data‑driven decision‑making by establishing architecture standards, reusable patterns, and interoperable data ecosystems across SAP, Salesforce, Informatica, Azure, Databricks, and related platforms. The role works closely with Enterprise Architecture, Security & Compliance, and Data Management teams to ensure standards are consistently applied across all data solutions.
Key responsibilities
- Data Architecture Strategy & Vision
- Develop an Align a Global Services Data Architecture vision across Global Deloitte Technology services and Member Firm environments
- Establish data architecture principles, standards, and reference architectures for data across Global Service applications and platforms
- Define a unified, cross‑data platform data architecture to address fragmentation across systems and geographies
- Establish interoperable data models and integration patterns to reduce duplication and data silos
- Develop architecture roadmaps aligned to business priorities, analytics, and AI enablement goals
- Ensure alignment with enterprise architecture standards and broader technology strategy
- Data Architecture Solutioning
- Provide architecture leadership for Global Services data initiatives and programs
- Provide architecture guidance for complex data transformation and analytics solutions
- Support architecture for data management services (MDM, metadata, data quality, lineage, cataloging)
- Ensure solution designs align with enterprise architecture principles and standard
- Establish reusable patterns for domain‑aligned, interoperable data products
- Ensure Global Data Products are analytics‑ and AI‑ready by design
- Guide lifecycle management of data products, including discoverability, quality, and governance
- Data Transformation & Analytics Enablement
- Provide architectural leadership for enterprise data transformation and analytics capabilities
- Define standards and reusable patterns for data transformation, modeling, and analytics integration
- Enable analytics‑ready data architectures supporting reporting, advanced analytics, and AI/ML use cases
- Partner with Global Services and Member Firms to co‑develop standards, best practices, and new data transformation and analytics patterns
- Drive consistency in how data is structured, transformed, and consumed across platforms
- Partner with Security and Compliance teams to co‑develop enterprise data security and privacy standards
- AI & Advanced Analytics Enablement
- Define data architecture patterns supporting AI/ML model development, deployment, and lifecycle management
- Ensure enterprise data assets are AI‑ready, including quality, accessibility, and governance
- Partner with AI/ML, analytics, and product teams to support use cases including generative AI, advanced analytics and intelligent automation
- Enable architectures that support AI‑enabled and component‑based data services
- Embed security‑by‑design and privacy‑by‑design principles into all data architectures
- Data Governance & Operating Model Alignment
- Align data architecture with enterprise data governance, quality, and compliance frameworks
- Define and enforce standards for data modeling, naming, classification, and lifecycle management
- Ensure governance controls are embedded into platforms via automation and policy enforcement
- Align architecture with evolving data and AI regulatory requirements
- Act as a strategic advisor on data and AI investments and enterprise transformation
Experience
- Proven years in enterprise data architecture, data engineering, or related roles
- Proven experience designing enterprise‑scale data architectures across multiple platforms
- Experience working in global, federated, or multi‑entity organizations
- Strong experience with SAP, Salesforce, Informatica, Azure, and Databricks
- Experience implementing Data Product and Data Mesh methodologies
- Experience of Data Visualization technology – Tableau, MS Fabric
- Experience designing data security and data privacy architectures
- Experienced with AI and Machine learning architectures, frameworks and standards
- Strong experience with data management practices (MDM, metadata, data quality, governance)
- Enterprise Architecture frameworks, eg TOGAF
Leadership & Business Skills
- Proven ability to influence stakeholders across global and member firm environments
- Strong communication skills to translate complex technical topics into business outcomes
- Experience engaging with senior stakeholders and cross‑functional teams
- Strategic thinking and ability to align architecture with business and AI priorities
Platform Expertise
- Modern data platforms, transformation pipelines, governance, and integration patterns
- Enterprise architecture frameworks and domain‑driven design principles
- Data Product and Data Mesh architectures
- Data transformation patterns (ETL/ELT, streaming, event‑driven)
- AI/ML data architecture and analytics enablement
- Modern data platforms (lakehouse, warehouse, streaming)
- Cloud platforms (Azure, Databricks; familiarity with others a plus)
- Data governance, security, compliance, and privacy controls
- Data integration, interoperability, and modular architecture patterns
Contact Details:
Hm Revenue & Customs (Hmrc) Recruitment Team
