Enterprise Data Architect
We are seeking a highly skilled Enterprise Data Architect to lead the development of data architecture across integration, data lakes, data warehousing, analytics, and governance. This role will bridge business requirements and technical delivery, providing architectural leadership, clear strategy, and hands-on design to support business intelligence, operational analytics, and regulatory compliance.
Key Responsibilities
* Develop and maintain enterprise-wide data architecture strategies ensuring scalability, security, availability, and alignment with organisational goals.
* Lead the design of data platforms, data integration with business application data warehouse/lakes, BI/reporting systems, and integration patterns (batch, streaming, APIs, microservices etc.).
* Develop conceptual, logical, and physical models across structured, semi-structured, and unstructured datasets using industry-standard techniques (Bill Inmon, Ralph Kimball, Data Vault etc.).
* Define and enforce standards for data quality, metadata management, security, privacy, and regulatory compliance (DAMA, OAIC APP, TOGAF, CMMI/DCAM, ISO Standards).
* Architect data solutions using Azure, Snowflake, Informatica and modern data stack including design for hybrid and multi-cloud environments.
* Partner with business stakeholders, enterprise architects, and delivery teams to translate business objectives into data-driven solutions.
* Map current state architectures to future state; manage roadmaps for modernisation, rationalisation, and optimisation of data assets.
* Guide the data engineering teams on best practices for CI/CD, automation, integration, and use of modelling tools (DEVOPS, VISIO, ERWIN or equivalent).
* Review and evaluate architecture effectiveness, scalability, and performance, recommending enhancements.
Requirements
* Minimum 10 years' experience in enterprise data architecture, solution design, and data management within non-profit industries or private/public organisations.
* Proven track record in architecting BI/reporting, integration architectures, and large-scale analytics platforms.
* Strong knowledge of cloud-native and hybrid solutions (Azure, AWS, Snowflake, Informatica, Databricks).
* Expertise in data modelling methodologies (Bill Inmon, Ralph Kimball, Data Vault 2.0 etc.) with practical use of Azure DevOps, Visio or other enterprise modelling tools.
* Hands-on experience in data engineering concepts including pipelines, CI/CD, orchestration, and DevOps integration.
* Deep understanding of data governance, metadata, data quality, and master/reference data management.
* Experience in modern integration approaches (APIs, event-driven design, streaming technologies).
* Proven ability to work within Agile/Scrum delivery environments.
* Excellent communication and stakeholder engagement skills, with demonstrated ability to translate technical concepts into business value.