Senior Software Engineer — Distributed Compute / Spark Systems

About the Role

Granica is hiring a Senior Software Engineer to build distributed compute systems for enterprise-scale data and AI workloads.

You will work on the core infrastructure behind Crunch, Granica’s continuous optimization product for enterprise lakehouse data. This includes systems for distributed execution, workload optimization, query performance, scheduling, resource management, and compute cost reduction across petabyte- and exabyte-scale environments.

You will own core systems that directly affect customer compute spend, query latency, workload reliability, cluster efficiency, and the performance of large-scale analytical data processing.

This is a hands-on systems role for engineers who have gone deep on distributed execution — particularly Apache Spark or similar query/runtime systems — and want to own performance, scheduling, reliability, and compute efficiency at massive scale.

What You’ll Do

Build and optimize distributed compute infrastructure for large-scale analytical and AI workloads

Improve execution performance across scans, joins, aggregations, shuffles, spills, caching, partitioning, and task scheduling

Design adaptive systems for workload routing, execution planning, resource allocation, and cluster efficiency

Debug bottlenecks across CPU, memory, network, storage, metadata, and distributed execution layers

Improve reliability, fault tolerance, and compute efficiency across Spark and adjacent systems such as Trino, Presto, Flink, Iceberg, Delta Lake, Hudi, and cloud object stores

What We’re Looking For

Deep engineering experience in distributed systems, query engines, databases, or cloud infrastructure

Production experience building, extending, or deeply optimizing distributed compute or query systems such as Spark, Spark SQL, Trino, Presto, Flink, or similar execution engines

Strong understanding of distributed execution, query planning, scheduling, resource management, fault tolerance, workload isolation, and performance optimization

Hands-on experience with Spark internals such as Catalyst, Adaptive Query Execution, shuffle, joins, aggregation, spill, memory management, or task scheduling

Strong programming skills in Scala, Java, Go, Rust, C++, or a similar systems-oriented language, with a pragmatic end-to-end builder mindset

Bonus

Contributions to Spark, Trino, Presto, Flink, Velox, DuckDB, DataFusion, Iceberg, Delta Lake, Hudi, Parquet, ORC, or related systems

Experience with cost-based optimization, vectorized execution, workload schedulers, execution control planes, resource managers, storage-aware execution, or adaptive query optimization

Research or open-source contributions in distributed systems, databases, query processing, data processing, or cloud infrastructure

Why Join Granica

Build foundational infrastructure for enterprise data and AI

Work on deep systems problems across distributed compute, query execution, scheduling, and compute efficiency

Own meaningful parts of the architecture in a small, high-caliber engineering team

Work directly with Product, Engineering, and company leadership

Have direct impact on customer performance, infrastructure cost, product direction, and company growth

Compensation & Benefits

Competitive salary, meaningful equity, and performance bonus for top performers

401(k) with company match, comprehensive health coverage, and unlimited PTO

Daily catered meals in our Mountain View office

Support for research, publication, and conference participation

At Granica, you'll help build the next generation of enterprise AI—from exabyte-scale data infrastructure, Large Tabular Models (LTMs), and stateful AI agents. Together, we're creating the infrastructure that enables enterprises to own their data, own the intelligence built on it, and scale both efficiently.