About Our Client Our client is a leading enterprise data platform company building an open, high-performance data lakehouse for AI and analytical workloads. The platform combines an intelligent SQL query engine, an AI-ready semantic layer, and an open catalog built on Apache Iceberg — enabling Fortune 500 companies across finance, energy, manufacturing, and logistics to unify, query, and govern data at massive scale across cloud and on-premise sources.

About the Role We are looking for a Senior Software Engineer for the team that owns the reliability and operational excellence of a large-scale data platform, delivered both as a cloud service and as self-managed software. You will work across the full platform — observability, security, control plane, and core services — diagnosing complex issues and delivering durable fixes across cloud, hybrid, and on-premises environments, in close collaboration with product engineering, SRE, support, and field teams. This is a backend platform engineering role focused on distributed systems reliability — not application development or CRUD services.

Responsibilities Investigate, diagnose, and resolve complex issues across cloud and self-managed deployments — distributed systems failures, performance degradation, and reliability incidents Own bug fixes and targeted improvements across core services, control plane, security, and observability infrastructure Support automated deployment and integration frameworks that enable consistent, repeatable delivery across cloud, hybrid, and on-premises environments Contribute to cluster lifecycle management, observability, and operational supportability capabilities Partner with SRE, support, and field teams to triage and resolve escalated customer issues Build runbooks, root cause analyses, and internal tooling that reduce time-to-resolution over time Collaborate with product engineering so that fixes are integrated back into the main codebase effectively

Required Qualifications Bachelor's or Master's degree in Computer Science or a related field, or equivalent experience 5+ years of software engineering experience with strong hands-on Java development at production scale Proficiency in Python and Bash for scripting, automation, and tooling Solid foundation in data structures, algorithms, and multi-threaded / asynchronous programming models Experience designing, debugging, and operating large-scale distributed systems or microservices Hands-on experience with Kubernetes and Docker across cloud, hybrid, or on-premises deployments Cloud-native development experience on one or more of AWS, Azure, or GCP Strong understanding of networking fundamentals (TCP/IP, DNS, HTTP) Clear communicator — able to explain problems, root causes, and solutions to technical and non-technical audiences Comfortable with AI-assisted development workflows — using modern AI tools productively while critically validating their output English Upper-Intermediate or higher (B2+) — daily written and verbal communication with a US-based engineering team Availability to work EU business hours shifted 2–3 hours later for daily overlap with US West Coast mornings Desired Skills Observability platforms: OpenTelemetry, distributed tracing, metrics, logging Background in data processing, data warehouse, data lake, or analytics systems Distributed file and object storage: S3, ADLS, or HDFS Infrastructure-as-code (Helm, Terraform) and CI/CD tooling (Jenkins, ArgoCD) Identity, authentication, and authorization systems: SSO, OAuth, SAML, RBAC NoSQL databases (MongoDB, RocksDB), Redis, or partner/OEM integration patterns Query processing, concurrency control, data replication, or storage systems

Details Engagement: Long-term contract Location: Europe (EU / EEA / UK), remote Working hours: EU business hours, shifted 2–3 hours later for daily overlap with the US West Coast team