Senior Database Engineer
TOPdesk builds service management software used across education, healthcare, government, and manufacturing. We are 800+ colleagues in 11 offices worldwide. Founded over 30 years ago, we serve more than 10 million users worldwide and have been helping organisations deliver better services ever since. We are an open, collaborative organisation with little hierarchy — people own their work end to end and are trusted to make the decisions that matter. We are reinventing ITSM and ESM for the agentic era, building AI agents our customers can trust, and this role is part of that. About the role As our Senior Database Engineer, you move TOPdesk from a reactive, outlier-hunting posture on database performance and cost to structural, proactive management of the Azure SQL estate — balancing performance, cost efficiency, and developer enablement across our hybrid SaaS environment. Azure SQL is a material portion of TOPdesk's hosting cost and the foundation of our customer-facing performance. Today, much of our optimisation happens when something breaks; this role gets ahead of that. Deep database performance engineering is a specialist craft, and this role brings it in-house as we decompose a long-tenured Java / MS SQL heritage platform into microservices. What this is not: A ticket-driven, request-by-request DBA role. The mission is structural ownership of the Azure SQL estate, not break-fix. On AI: Deep database expertise is the primary selection criterion. Familiarity with AI-assisted analysis and automation is beneficial and will be developed further in role — we are an increasingly agentic engineering organisation, and you will have the support to grow that practice. Who you work with You sit in the Deploy, Run & Optimize lane, reporting to the Engineering Manager for Cloud & SRE, and partner across the teams driving heritage-platform decomposition — bringing deep specialist ownership where database craft is currently spread thin. What you'll do Own the estate Cost and resource optimisation. Find the inefficiencies — noisy neighbours, abusive API usage, sub-optimal allocation — that drive Azure SQL cost, and implement structural savings. Performance engineering. Monitor query response times and execution plans structurally; own index hygiene — remove redundant indexes, add smarter ones for heavy API traffic. Observability. Query tagging and monitoring so the business sees which services and customers drive load and cost. Resilience and security. Own backup and restore validation and disaster-recovery testing for the SQL estate; partner with Cloud & SRE on high availability, patching and lifecycle, privileged access, and database security. Enable engineering teams Advise teams so they own their data solutions well and prevent data-layer debt accumulating across new microservices. Move toward a model where domain teams keep strong cont...