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 Middle-level Software Engineer to work on the core query engine of a large-scale distributed data platform. You will develop features across query planning, optimization, and execution, contribute to performance-critical components, and help investigate and fix production issues reported by real enterprise customers. This is a systems-level, backend engineering role focused on distributed data processing internals — not application development or CRUD services.

Responsibilities: Develop and maintain features across the query engine — planning, optimization, execution, and data access layers Write performance-conscious code in Java and/or C++ Investigate and fix production and customer-reported issues under the guidance of senior engineers, including fixes delivered across multiple supported release lines Work with SQL semantics, query plans, and execution operators over large-scale distributed data Integrate with columnar formats, open table formats, and connectivity drivers Contribute to CI/CD and automated testing in Jenkins Deploy and validate changes on Kubernetes (GKE/EKS/AKS) across GCP, AWS, or Azure with Docker Debug issues across query planning, distributed execution, memory management, and I/O; collaborate with US-based teams on design and code reviews.

Required Qualifications: B.S. or M.S. in Computer Science, Computer Engineering, or a related field 3+ years in backend / systems software engineering Strong proficiency in Java or C++ with solid OOP and software design fundamentals, including concurrency and asynchronous programming (comfort with both languages is especially valued) Strong SQL and understanding of relational and analytical data systems, including query execution concepts Hands-on experience with data processing systems: query engines, distributed databases, ETL/ELT, or analytical platforms Experience with Jenkins pipelines and modern development workflows Docker and basic Kubernetes (running workloads, debugging pods, kubectl fluency) Hands-on experience with at least one major cloud (GCP, AWS, or Azure) Confident Git/GitHub workflows Comfortable with AI-assisted development workflows — using modern AI tools for code comprehension, debugging, and test generation, and 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: Apache Arrow (columnar in-memory format) and SQL planner/optimizer frameworks such as Apache Calcite LLVM-based runtime expression compilation Open table formats — Apache Iceberg, Delta Lake, or Hudi — and columnar file formats such as Parquet, Avro, or ORC MPP query engines (Presto, Trino, or similar); exposure to distributed data platforms such as Spark, Snowflake, or Databricks Messaging systems: Kafka, NATS, or cloud pub/sub services Query planning, optimization, and execution internals Connectivity drivers: JDBC, ODBC, Arrow Flight Managed Kubernetes (GKE/EKS/AKS), multi-cloud exposure; Terraform Performance profiling of latency-sensitive 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