Software Engineer - Query Execution

About the role

Be Part of Building the Future

the company is the unified lakehouse platform for self-service analytics and AI, serving hundreds of global enterprises, including Maersk, Amazon, Regeneron, NetApp, and S&P Global. Customers rely on the company for cloud, hybrid, and on-prem lakehouses to power their data mesh, data warehouse migration, data virtualization, and unified data access use cases. Based on open source technologies, including Apache Iceberg and Apache Arrow, the company provides an open lakehouse architecture enabling the fastest time to insight and platform flexibility at a fraction of the cost. Learn more at [application details available after applying]

About the role the company’s Query Execution team builds the runtime responsible for executing analytical queries at scale. The team sits between query planning and table scans, building the systems that turn query plans into efficient, reliable execution.

As a Software Engineer, you’ll work with experienced engineers to build, test, and support well-scoped improvements to the execution engine. You’ll learn how the company’s query runtime works while contributing to areas such as query operators, expression evaluation, memory management, scheduling, and performance.

What you’ll be doing

• Build and support execution-engine components: Implement, test, debug, and maintain well-defined changes to query operators, expression evaluation, execution scheduling, and resource management.
• Develop reliable software: Write clear, maintainable Java code; add unit and integration tests; and follow established engineering practices for code review, testing, and documentation.
• Investigate issues: Help diagnose query correctness, reliability, and performance issues using query profiles, logs, telemetry, benchmarks, and production data.
• Learn runtime and performance fundamentals: Build familiarity with vectorized processing, concurrency, memory usage, parallelism, data exchange, and disk spilling.
• Collaborate with the team: Work closely with senior engineers and partner teams to understand requirements, break work into manageable tasks, and deliver incremental improvements.
• Use AI-assisted development tools: Apply AI tools to code comprehension, debugging, test generation, and documentation, while validating results through testing, review, and sound engineering judgment.
• Grow your engineering skills: Participate actively in design discussions and code reviews, seek feedback, and steadily take on broader technical responsibility.

What we’re looking for