Enterprise Data Architect

Vallum Associates
London, United Kingdom
3 weeks ago
Applications closed

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Job Type
Permanent
Work Pattern
Full-time
Work Location
On-site
Seniority
Senior
Education
Degree
Posted
18 May 2026 (3 weeks ago)

Responsibilities

1. Define and drive enterprise-wide cloud and data architecture strategies, roadmaps, and governance frameworks aligned to business objectives.

2. Design and implement scalable, secure, and resilient cloud-native solutions across Microsoft Azure Azure, Amazon Web Services AWS, and Google Cloud GCP environments.

3. Lead cloud transformation and migration initiatives including hybrid cloud and multi-cloud architectures.

4. Establish and oversee enterprise data architecture frameworks such as Data Mesh, Lakehouse, and Data Fabric.

5. Drive adoption of modern architecture patterns including microservices, APIs, event-driven architectures, and real-time data processing.

6. Define and enforce architecture standards, security controls, compliance policies, and governance best practices.

7. Collaborate with business stakeholders, product owners, engineers, and platform teams to deliver scalable and efficient technology solutions.

8. Identify opportunities to modernise platforms, reduce technical debt, improve performance, and optimise cloud and operational costs.

Required Skills

1. Extensive experience in Enterprise Architecture, Cloud Architecture, or Data Architecture within large-scale enterprise environments.

2. Strong expertise in cloud platforms including Microsoft Azure Azure, Amazon Web Services AWS, and Google Cloud GCP.

3. Proven experience designing cloud-native, scalable, secure, and highly available enterprise solutions.

4. Strong knowledge of modern data platforms and technologies including Data Lakes, Lakehouse, ETL/ELT, Kafka, and Spark.

5. Expertise in microservices, APIs, event-driven architectures, integration patterns, and distributed systems design.

6. Good understanding of data governance, cloud security, compliance frameworks, and enterprise risk management.

7. Experience with DevOps, CI/CD pipelines, Infrastructure-as-Code, Kubernetes, Docker, and automation practices.

8. Strong stakeholder management, communication, analytical, and problem-solving skills with the ability to influence technical and business decision

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Where to advertise data science jobs UK in 2026: the specialist boards, communities and channels that actually reach senior and lead data science talent. Data science spans a broad and often misunderstood spectrum — from statistical modelling and experimental design through to machine learning engineering, product analytics and AI research. The strongest candidates identify firmly with specific subdisciplines and are frustrated by adverts that conflate data scientist with data analyst, business intelligence developer or machine learning engineer. General job boards produce high application volumes for data roles but consistently fail to match specialist data science profiles with the right opportunities. This guide, published by DataScienceJobs.co.uk, covers where to advertise data science roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about hiring across different role types.