Data Platform Engineer

Overview

In this role you will design and build cloud-native data platform capabilities to unlock business value across data engineering, BI, analytics, and AI/ML workloads. You will work with cross-functional teams to deliver scalable, secure, and cost-efficient platform components aligned to modern engineering practices. You help drive a data-driven culture by enabling self-service data capabilities and robust observability. This is an opportunity to shape data platform strategy within Quilter’s COO data agenda and support large-scale growth.

Pay / Benefits

• 182 hours holiday
• Pension scheme
• Private medical insurance
• Life assurance 4x salary
• Income protection 75% of salary
• Flexible benefits available to UK employees

Responsibilities

• Design and implement cloud-native data platform capabilities for data engineering, BI, analytics, and AI/ML workloads
• Ensure solutions follow cloud platform engineering standards, patterns, and best practices for reliability and cost-efficiency
• Deliver robust, reusable, well-documented platform components aligned to business objectives (IaC, CI/CD, DevOps)
• Embed security-by-design principles across platform components (identity, access control, encryption, network security)
• Collaborate with product managers, data engineers, analysts, data scientists, and stakeholders to define requirements and priorities
• Coordinate with cloud engineering, security, and enterprise architecture teams to align with broader tech strategy and platform roadmap
• Work with platform tenant teams to improve onboarding, delivery processes, and self-service capabilities
• Translate business and analytical needs into clear engineering plans and deliverables
• Communicate with both technical and non-technical stakeholders on priorities, risks, and progress
• Monitor, alert, and manage incidents to ensure high availability and performance of data platforms
• Continuously improve deployment pipelines and engineering productivity
• Support observability through logging, metrics, and tracing for rapid troubleshooting

Key requirements

• Degree in a technical discipline or equivalent practical experience
• Strong hands-on experience designing and maintaining data platforms in Azure, Databricks, and Fabric ecosystems
• Experience delivering federated data capabilities with standards and guardrails
• Experience automating delivery through IaC and deployment pipelines
• Experience monitoring, logging, alerting, and improving platform reliability and performance
• Understanding of cloud security best practices and secure data access/privacy controls

• Strategic thinker with problem-solving ability
• Clear and concise communicator with both technical and non-technical stakeholders
• Collaborative mindset and cross-functional teamwork
• Terraform, Python, SQL, PowerShell
• Azure DevOps pipelines for data platform deployments
• Databricks: Delta Lake, Unity Catalog, Workflows, Notebooks, Clusters, MLflow

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