Senior Database Engineer

Xebia is a global AI-first, digital transformation, and engineering partner. With over 25 years of experience and a team of 5,000 professionals across 16 countries, we help organizations design and build scalable products, platforms, and data-driven solutions. We specialize in Artificial Intelligence, Data and Cloud, Intelligent Automation, and Digital Products, combining deep technical expertise with a strong focus on engineering excellence and a people-first culture. In the CEE region, we’re a team of nearly 1,000 experts delivering modern applications, data platforms, and AI solutions for clients such as McLaren, Aviva, Deloitte, Spotify, Disney, ING, UPS, Tesco, Truecaller, AllSaints, Volotea, Schmitz Cargobull, Allegro, InPost, and many, many more. We work with leading technologies including AWS, Azure, GCP, Databricks, and Snowflake, and combine strong engineering culture with a consulting mindset and a continuous focus on growth and knowledge sharing. About Project This position is an exciting opportunity to own the full lifecycle (administration, automation, and troubleshooting) of our critical database systems operating within a large-scale, multi-tenant Kubernetes environment. You will be essential in driving our GitOps and Helm-centric deployment strategy, focusing on ensuring zero-downtime upgrades and maximizing performance and stability for our core platform services. This role offers the perfect opportunity to hone your skills and gain direct exposure to advanced cloud database architecture and container orchestration challenges. You will be: designing, implementing, and maintaining database infrastructure using StatefulSets, Operators, and Helm charts to ensure databases are reliable, self-healing, and scalable, owning the deployment lifecycle for database clusters by managing version control for Helm charts and configuration templates, supporting and administering production database systems by proactively instrumenting and monitoring performance, security, and availability within the containerized environment, performing zero-downtime upgrades and migrations for major and minor releases, developing and maintaining Helm hooks and custom scripts to automate complex stateful operations, managing and optimizing performance for backend data stores, ensuring data consistency and integrity across pod life cycles, developing and maintaining automation tools and scripts (Bash, Python) specifically focused on simplifying Kubernetes management tasks, such as provisioning users/secrets and monitoring cluster state. Your profile: 4+ years of experience managing large-scale, high-availability database systems (PostgreSQL / MongoDB), experience with Python or Bash automation scripting, proven experience with Kubernetes & Helm. good verbal and written communication skills in English (min. B2+). Work from the European Union region and a work permit are required. Nice to have: knowledge of advanced PostgreSQL HA concepts (e.g., streaming replication, Repmgr/Patroni) and/or MongoDB sharding and replication, experience with AWS, GCP, or Azure, experience in using version control systems, configuration management tools and IaaC such as Terraform, CloudFormation, experience using database tools such as pgAdmin, Pgbench, Robo3t, Studio3t, MongoDB Ops Manager and Mongo mirror, experience with prometheus, cloudwatch and monitoring tools both within kubernetes and external cloud managed infrastructure, experience applying GenAI in a more structured way within the SDLC, including defined workflows, prompt patterns, or tool integrations embedded into daily work, interest in and familiarity with emerging AI-driven practices (e.g. agent-based workflows, automation patterns, AI-augmented development), with a willingness to explore and experiment beyond standard approach. Recruitment Process CV review – HR call – Technical Interview – Client Interview I - Client Interview II – Hiring Manager Interview – Decision Apply To This Job