Middle Software Engineer — Query Engine / Data Platform

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)