WPP Media
Lead Architect, Data & AI Platforms
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About WPP Media
WPP is the trusted growth partner for the world’s leading brands. With exceptional talent, trusted data and intelligence, and world-class partnerships – all united by our pioneering agentic marketing platform, WPP Open – we help clients navigate change, capture opportunity, and deliver transformational growth.
WPP Media is WPP's AI-driven media operating unit, bringing together media, data, and partnerships to deliver creative personalisation at scale. Connected through WPP Open and powered by Open Intelligence, clients see exactly where, how, and why their media investment is working.
For more information, visit wppmedia.com.
309 - Lead Architect, Data & AI Platforms – Choreograph Consulting
About WPP Media
WPP is the creative transformation company. We use the power of creativity to build better futures for our people, planet, clients and communities. For more information, visit wpp.com.
WPP Media is WPP’s global media collective. In a world where media is everywhere and in everything, we bring the best platform, people, and partners together to create limitless opportunities for growth. For more information, visit wppmedia.com
About Choreograph: A Leading WPP Media Brand
Choreograph is WPP’s global data products and technology company. We’re on a mission to transform marketing by building the fastest, most connected data platform that bridges marketing strategy to scaled activation.
We work with agencies and clients to transform the value of data by bringing together technology, data and analytics capabilities. We deliver this through the Open Media Studio, an AI-enabled media and data platform for the next era of advertising.
We’re endlessly curious. Our team of thinkers, builders, creators and problem solvers are over 1,000 strong, across 20 markets around the world.
Role Summary And Impact
We are hiring a Lead Architect to own the technical design of Azure-first data and AI platforms. You will define the reusable patterns, reference architectures and end-to-end solution concepts that our delivery teams build from, and prove them in code rather than in slideware.
This is an engineering-first, developer-architect role: roughly 70–80% designing solutions, building and packaging reusable patterns, and prototyping new concepts in code, and 20–30% client-facing advisory.
As a senior technical authority, you will bridge client strategy with hands-on code, setting the reference architecture and proving it yourself, then partnering with the Data Engineering, Platform/DevOps, Security and Client Delivery teams who industrialise it into resilient, self-service, cost-effective and compliant delivery at scale. Replacing traditional IT operations and manual governance with modern software automation, you will mentor engineers, review code/IaC, and own key technical decisions and trade-offs.
What this role is not: This is not an IT infrastructure, cloud operations or estate-management position. There is no BAU support rota, ticket queue, or manual portal configuration. Candidates whose recent experience is running and supporting cloud infrastructure, rather than designing and building data and AI platforms in code, will not be a fit. Equally, this is not a hands-off design role: you will prototype and prove your own patterns before a delivery team scales them.
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Area Of Expertise:
- Infrastructure-as-Code (IaC) & Automation: Production fluency with Terraform; treating IaC like software code using modular designs, policy-as-code, reusable baselines, and automated testing via CI/CD (GitHub Actions / Azure DevOps).
- Solution Architecture Pattern Design & Packaging: Defining end-to-end solution concepts and reference architectures, then packaging them as deployable, versioned assets that other teams can pick up and run, rather than as documents.
- Azure-First Data Platforms: Deep architecture and build experience on Microsoft Azure (Data Lake/Lakehouse patterns, ADLS Gen2, Synapse Analytics, Azure Databricks, Delta Lake), with enough hands-on AWS or Google Cloud Platform (GCP) experience to design portable patterns for mixed client estates.
- Orchestration & Data Pipelines: Batch and streaming ingestion using Azure Data Factory (pipelines, wrangling flows, integration runtimes), Event Hubs, Kafka, and performance optimization (Spark/Synapse SQL).
- AI Solution Design & Build: Designing and building AI solutions on the data platform: Agentic AI workflows, RAG (Retrieval-Augmented Generation) patterns, vector search and LLM orchestration, alongside standard analytical workloads.
- Security as Code: Networking, private endpoints, managed identities, Key Vault, RBAC, Purview governance and data masking, all defined in Terraform and versioned like application code.
- Observability, FinOps & Operations: Azure Monitor, Log Analytics, cost/performance telemetry, SLAs/SLOs for pipelines, and FinOps-aware cloud design.
- API & Service Integration: Designing data services using Azure Functions, Logic Apps, and API Management.
Skills And Experience:
At WPP Media, we believe in the power of our culture and our people. It’s what elevates us to deliver exceptional experiences for both our clients and each other. In this role it will be critical to embrace WPP & WPP Media’s shared core values:
- Be Extraordinary by Leading Collectively to Inspire transformational Creativity.
- Create an Open environment by Balancing People and Client Experiences by Cultivating Trust.
- Lead Optimistically by Championing Growth and Development to Mobilize the Enterprise.
- Developer-Architect Mindset: A hands-on builder who sets reference architectures and patterns, leading by example through direct code contributions and rigorous code/IaC reviews.
- 70/30 Design-to-Advise Split: Spends 70–80% of the time architecting solutions, writing code, packaging repeatable patterns and prototyping new concepts, drawing on end-to-end understanding of the data platform in use, and 20–30% in front of clients, translating commercial objectives into technical roadmaps and explaining trade-offs to non-technical stakeholders in their own language.
- Coding & Automation Obsession: Strong scripting/programming skills (Python, SQL, Terraform); automates everything possible via IaC and CI/CD, favoring repeatability over legacy IT ticket processes.
- Azure-Deep, Cross-Cloud Aware: Expert on Azure and comfortable across AWS and GCP, designing for operability, security, and cost while preparing platforms for emerging AI architectures.
- Clear Communicator & Mentor: Able to facilitate client workshops, write concise design docs/runbooks, align cross-functional teams, and mentor engineers to create shared ownership of outcomes.
- Outcome-Focused: Measures success with deployment frequency, lead time for changes, data pipeline SLAs, cost efficiency, and platform reliability metrics.
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Responsibilities:
- Lead Azure-First Platform Architecture: Architect and implement Azure data platforms for clients, including landing zones, networking, identity, and data platform services (Azure Data Lake Storage, Synapse, Databricks), extending patterns to AWS or GCP where a client estate requires it.
- Design & Build Data Pipelines: Design, Implement key data ingress patterns across data platforms. Key focus would be Azure Data Factory pipelines and data flows for ingestion, transformation, and orchestration; establish patterns for parameterization, retries, and error handling to meet pipeline SLAs, then work with the Data Engineering team to scale those patterns into production delivery.
- Implement Modern IaC & CI/CD: Design, implement key IaC patterns. Deliver infrastructure-as-code using Terraform; create reusable modules and policy-as-code guardrails. Establish repo strategies, branching, pull requests, multi-stage pipelines, approvals, and automated promotion gates.
- Package Reusable Solutions: Turn proven designs into packaged, deployable assets (Terraform modules, pipeline templates, reference implementations and accelerators) with the documentation and worked examples delivery teams need to reuse them across clients.
- Architect for AI & DataOps: Introduce DataOps practices (automated unit/integration testing, data quality checks) and build the AI layer on top of it: vector search, RAG workflows and agentic capabilities.
- Prototype & Showcase New Concepts: Build working prototypes of new data and AI concepts (RAG, agentic workflows, streaming and real-time patterns) and demonstrate them to clients to shape demand, test feasibility and de-risk delivery before a full team is committed.
- Client Advisory & Technical Leadership: Own the technical relationship with client and agency stakeholders. Run discovery and design workshops, present at design authorities, and translate commercial objectives into phased roadmaps, costs and trade-offs that a non-technical audience can act on.
- Ship Secure-by-Default Controls: Codify private endpoints, managed identities, Key Vault-backed secrets, RBAC, network isolation, data encryption and Purview cataloging/lineage as reusable modules, so security ships with the platform rather than being applied afterwards.
- Optimize Performance & Cost (FinOps): Optimize compute and storage across Spark clusters, autoscaling, partitioning, and serverless options; track, report, and drive cloud cost savings.
- Observability & Reliability: Build monitoring into pipelines and platforms using Azure Monitor and Log Analytics, and define the SLOs and alerting the owning engineering team runs against.
- Guide Event-Driven Architectures: Lead streaming and micro-batch patterns (Event Hubs, Kafka
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