Working hours: EU business hours, shifted 2–3 hours later to ensure daily overlap with US West Coast (PST/PDT) mornings About the 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 to design, build, and own significant components of the core query engine of a large-scale distributed data platform. You will lead work across query planning, optimization, and execution — driving architectural decisions, mentoring middle engineers, and pushing the platform’s performance and scalability boundaries across all major clouds.
This is a systems-level, backend engineering role focused on distributed data processing internals — not application development or CRUD services. Responsibilities * Architect, design, and implement significant components of the query engine — planner, optimizer, execution operators, memory management, and data access layers. * Write and review high-quality, performance-critical code in Java and/or C++. * Own end-to-end delivery of features from technical design through production rollout. * Drive performance optimization work — profiling, benchmarking, and eliminating bottlenecks in latency- and throughput-sensitive paths. * Integrate deeply with columnar formats, open table formats, and connectivity drivers. * Mentor middle engineers, lead code reviews, and set technical standards for the team. * Contribute to CI/CD architecture and quality processes across Jenkins, containerization, and multi-cloud deployment (GCP, AWS, Azure via Kubernetes / Docker). * Debug complex, cross-layer issues spanning query planning, distributed execution, memory management, and I/O. * Partner with US-based engineering leads on design reviews, architectural decisions, and roadmap execution.
Required Qualifications * Education: B.S. or M.S. in Computer Science, Computer Engineering, or a related technical field. * Programming: Strong proficiency in Java or C++, with deep understanding of OOP, systems design, memory management, and concurrency. Candidates strong in both are especially valued. * SQL & Data: Advanced SQL skills and strong understanding of query execution internals — planning, optimization, and operator implementation. * Data processing systems experience: Demonstrated experience building or extending data processing systems — query engines, distributed databases, ETL/ELT frameworks, or analytical platforms. * Engineering experience: 5+ years in backend/systems software engineering, with a track record of owning significant components. * CI/CD & DevOps: Solid experience with Jenkins and modern engineering workflows. * Containers & Orchestration: Strong working knowledge of Docker and Kubernetes. * Cloud: Hands-on experience with at least one major cloud (GCP, AWS, or Azure); exposure to more than one is a strong plus. * Version Control: Confident with Git / GitHub workflows and rigorous code review practices. * English: Upper-Intermediate or higher (B2+) — daily written and verbal communication with a US-based engineering team. * Availability: Able to work EU hours with a 2–3 hour shift toward US West Coast time to ensure daily overlap with the client team. * Leadership: Prior experience mentoring engineers, leading technical designs, or owning components end-to-end.
Desired Skills * Deep experience with Apache Arrow (columnar in-memory format). * Hands-on experience with Apache Calcite (SQL parsing, planning, optimization framework). * Experience with Gandiva or LLVM-based expression compilation and code generation. * Experience with open table formats — Apache Iceberg, Delta Lake, or Hudi. * Deep familiarity with distributed computing frameworks (e.g., Apache Spark, Kafka) and MPP SQL query engines (e.g., Presto, Trino, or similar). * Deep understanding of query planning, optimization (cost-based, rule-based), and execution internals. * Experience with data connectivity drivers: JDBC, ODBC, Arrow Flight. * Kubernetes on managed services (GKE / EKS / AKS) and multi-cloud exposure. * IaC tools such as Terraform. * Track record of performance optimization at the systems level — profiling, vectorization, cache/memory-conscious design. * Prior experience contributing to open-source data infrastructure projects.
