AI & Data Architect — Cloud-Native, Enterprise Data

eFinancialCareers

Greater London

Hybrid

GBP 60,000 - 85,000

Full time

6 days ago

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Benefits offered by this job

Hybrid working

Job summary

eFinancialCareers in Central London is seeking an experienced AI & Data Architect to lead the design and delivery of enterprise-scale data solutions. You will build cloud-native architectures, enable AI-driven insights, and help organizations unlock data value.

You will work with business and technology leaders to architect analytics, governance and digital transformation programmes across multiple industries, translating complex concepts for senior stakeholders.

Qualifications

Proven experience designing and delivering enterprise data architecture solutions.
Strong background building cloud-based data platforms, ETL pipelines and data engineering solutions.
Expertise with Azure, AWS or Google Cloud data services and modern data platforms.
Experience with data modelling techniques including dimensional, relational or Data Vault modelling.
Knowledge of data governance, metadata management and data quality frameworks.
Experience working with AI and machine learning within data platforms, alongside an understanding of AI governance.
Familiarity with platforms such as Snowflake or Microsoft Fabric.
Experience delivering analytics and reporting solutions using tools such as Power BI, Tableau or Looker.
Strong stakeholder management skills with the ability to communicate complex technical solutions to both technical and non-technical audiences.
Previous experience leading projects, workstreams or technical teams.

Responsibilities

Design and deliver end-to-end data architecture solutions aligned to business objectives.
Build scalable data platforms, pipelines and ETL processes across modern cloud environments.
Develop conceptual, logical and physical data models, including dimensional and relational modelling.
Integrate modern cloud platforms with legacy systems to enable seamless data access and reporting.
Establish architecture standards covering security, governance, scalability, performance and cost optimisation.
Lead technical design, architecture governance and best practice across multiple data initiatives.
Implement robust data governance and quality frameworks to ensure trusted, compliant data.
Apply AI technologies to enhance data solutions through intelligent automation, predictive monitoring and advanced analytics.
Translate complex technical concepts into clear recommendations for senior business stakeholders.
Mentor technical teams and champion emerging technologies, tools and architecture approaches.