Platform Engineer

London Stock Exchange; Greater London; On-site; GBP 85,000 - 120,000; Full time

Job summary

London Stock Exchange is seeking a DevOps Engineer to design, build, and maintain scalable cloud infrastructure on Microsoft Azure for data platforms such as Databricks, Event Hubs and ADLS Gen2. You will implement infrastructure-as-code, automation, and modern DevOps practices to streamline deployments, ensure reliability of real-time and batch data workloads, and optimize costs.

Collaborate with engineering and data teams to enable DevOps best practices and maintain secure, cost-effective

Qualifications

• Experience designing and implementing IaC with Terraform.
• Hands-on experience with Azure cloud services and security practices.
• Strong Linux system administration and scripting skills.
• Proficiency in Python and Bash for automation.
• Solid SQL skills for data workflows and performance tuning.
• Experience with data-centric platforms: Databricks, Event Hubs, ADLS/Blob storage.
• Familiarity with containerization (Docker/Kubernetes) and CI/CD tooling.
• Experience with monitoring and log management tools (Datadog, Splunk).
• Version control with Git (GitHub/GitLab) and Azure DevOps.

Responsibilities

• Design, build, and maintain scalable Azure cloud infrastructure.
• Automate data platform workloads and deployment pipelines.
• Support real-time and batch data workloads with reliable CI/CD.
• Manage and optimize Azure-native data services and SQL platforms.
• Implement security, governance, and cost-optimization across resources.
• Collaborate with engineering and data teams to enable DevOps best practices.
• Troubleshoot production issues and ensure high availability.

Skills

Python

Bash scripting

SQL

Linux

CI/CD

Event-driven

Tools

Terraform

Azure

Databricks

Azure Event Hubs

Azure Storage

Azure SQL

PostgreSQL

Docker

Kubernetes

Git

GitHub

GitLab

Azure DevOps

Datadog

Splunk

Bash

Python

Linux

Job description

Responsibilities

• We are seeking a highly skilled DevOps Engineer to design, build, and maintain scalable, secure, and high-performing cloud infrastructure on Microsoft Azure
• This role is heavily focused on enabling data platforms—including Databricks, Event Hubs, and Azure Storage—through infrastructure-as-code, automation, and modern DevOps practices
• You will work closely with engineering, data, and platform teams to streamline deployment pipelines, ensure reliability of data services, and support both real-time and batch data workloads
• Design, implement, and manage cloud infrastructure solutions using Terraform (Infrastructure-as-Code)
• Build and maintain CI/CD pipelines for applications and data platforms
• Deploy and support Azure-native data services including Azure Databricks, Azure Event Hubs, Azure Storage (ADLS Gen2, Blob)
• Manage and optimize SQL-based systems (Azure SQL / PostgreSQL / related platforms)
• Automate operational tasks using Bash scripting and other scripting tools
• Administer and maintain Linux-based environments
• Monitor system performance, reliability, and costs; implement improvements and optimizations
• Ensure security, compliance, and governance across all Azure resources
• Work with development and data engineering teams to enable DevOps best practices
• Troubleshoot production issues and ensure high availability of critical systems
• Support real-time data pipelines and streaming architectures

Qualifications

• CI/CD tools (GitLab, GitHub, Azure DevOps, or similar)
• Strong hands‑on experience with: Terraform (mandatory)
• Knowledge of security best practices in Azure (RBAC, managed identities, Key Vault)
• Solid experience with Linux system administration
• Strong Python and Bash scripting skills
• Proficiency in SQL (querying, performance tuning, data workflows)
• Infrastructure automation and configuration management
• Experience with data‑centric platforms: Azure Databricks, Azure Event Hubs, Azure Storage (ADLS Gen2 / Blob)
• Exposure to containerization (Docker, Kubernetes)
• Monitoring, logging, and alerting tools like Datadog, Splunk, etc.
• Version control systems (Git)
• Microsoft Azure (core services + networking + security)
• Development experience with streaming data architectures and event‑driven systems
• Familiarity with data lake / Lakehouse based big data systems and architectures
• Experience in high‑throughput, low‑latency environments