Platform Architect

Platform Architect role

Start Date: 26th August 2026

End Date: 1st February 2027

Rate: £500 - £550

Location: London, UK

N# of Days onsite P/W: 3

N# of Seats Available: 1

Role Purpose

We are seeking a highly experienced, hands-on Azure Databricks Platform Engineer / Architect to enhance and optimise an enterprise Data Platform. This role combines architecture, engineering, operational support and platform optimisation. The successful candidate must be capable of designing, configuring, developing, troubleshooting and improving Azure Databricks solutions, rather than operating solely at a strategic or governance level.

The role focuses on three primary outcomes:

• Enabling and optimising Databricks Serverless capabilities.
• Strengthening FinOps practices, cost controls and platform governance.
• Enhancing the Databricks Discovery Zone to support migration and consolidation of workloads currently delivered through POSIT/RStudio.

Key Responsibilities

1. Databricks Serverless Enablement and Optimisation

• Assess existing workloads and determine the most appropriate compute model, including Serverless, Jobs Compute, Interactive Compute or Classic Clusters, based on workload characteristics, SLA requirements, performance, utilisation and cost.
• Configure and implement Serverless capabilities for notebooks, jobs, SQL workloads, analytical processing and data pipelines.
• Develop workload placement standards and guidance, identifying scenarios where Serverless may not be the most cost-effective solution for predictable, long-running or continuously utilised workloads.
• Implement compute policies, autoscaling configurations, quotas, budget controls and operational guardrails.
• Monitor performance and cost, identifying oversized, underutilised or idle resources and recommending optimisation opportunities.

1. FinOps and Enterprise Platform Controls

• Define and implement a practical FinOps operating model covering ownership, accountability, environments, projects, applications, cost centres and teams.
• Establish mandatory tagging standards and integrate automated validation into CI/CD pipelines to prevent deployment of non-compliant resources.
• Deliver granular cost attribution and reporting across workspaces, projects, applications, workloads and business teams.
• Configure budgets, spend thresholds, alerts and usage monitoring to proactively manage platform costs.
• Analyse platform usage and billing data to identify cost anomalies, inefficient workloads, excessive storage consumption, unnecessary data movement and underutilised resources.
• Support continuous improvement through cost optimisation recommendations and governance controls.

1. Discovery Zone Enhancement and POSIT/RStudio Migration

• Enhance the Databricks Discovery Zone to support the migration and modernisation of analytics and data science workloads currently running on POSIT/RStudio.
• Enable capabilities including:
• Secure API and external system integrations
• Application deployment and operationalisation
• External data ingestion
• BI and reporting connectivity
• Scheduling and orchestration
• Local IDE-based development
• LLM and AI integration
• Operational monitoring and reporting
• Define reusable onboarding, migration and delivery patterns that reduce technology sprawl while improving platform security, supportability and delivery speed.
• Collaborate with stakeholders to support migration planning, solution design and adoption.

1. Data Engineering and Integration

• Design, build and optimise scalable data ingestion and transformation solutions using Python, PySpark, SQL and Delta Lake.
• Implement batch and incremental processing patterns, including Change Data Capture (CDC), schema evolution, reconciliation processes, data quality controls and error handling.
• Develop reusable integration frameworks for:
• REST APIs
• SaaS platforms
• Databases
• Files and object storage
• Document repositories
• Enterprise systems
• External and public data sources
• Implement secure authentication, secrets management and credential handling practices.
• Deliver end-to-end data flows from source ingestion through governed and curated data layers, supporting analytics, BI, machine learning and application consumption.

Azure & Databricks Platform

• Deep hands-on Azure Databricks implementation, administration and troubleshooting experience.
• Databricks Serverless architecture, workload placement and compute optimisation.
• Azure networking, identity, security, monitoring, secrets management and private connectivity.
• Databricks SQL, Delta Lake and query/workload performance optimisation.
• Strong understanding of platform governance, operational support and best practices.

Highly Desirable

• Experience migrating workloads from POSIT/RStudio to Databricks.
• Migration of analytical and data science solutions, including conversion of R-based workloads and libraries.
• AI/ML experience, including LLM integration, RAG/vector retrieval, model serving and model lifecycle management.
• Experience delivering large-scale platform transformation programmes.
• Strong Azure and Databricks FinOps experience, including cost optimisation, governance and chargeback/showback models.
• Experience operating within highly regulated or complex enterprise environments.

If you receive suspicious outreach claiming to be from us, please contact us via the ManpowerGroup website.