Technical leadership role at Granica, architecting distributed data systems and evolving AI infrastructure. Collaborate with teams for system design and efficiency improvements in large-scale environments.
Responsibilities
Architect and lead the evolution of Granica’s distributed data systems—catalogs, metadata stores, ACID layers, schema evolution frameworks.
Advance data and storage efficiency. Design adaptive compaction, caching, and indexing strategies that minimize I/O and latency.
Drive platform reliability & observability. Define SLOs, chaos drills, and metrics frameworks across Spark/Kafka/Flink fleets.
Mentor and scale teams. Conduct design reviews, set technical standards, and guide high-impact engineers.
Collaborate with AI infra & research. Align platform evolution with model training and inference data needs.
Publish and represent Granica externally. Contribute to research or OSS; help shape the future of AI-scale data systems.
Requirements
7+ years in distributed systems, storage, or large-scale data infrastructure.
Deep expertise in system design, scalability, and performance optimization.
Strong coding skills in Java, Scala, Go, or C++, with disciplined testing and observability.
Proven leadership across cross-functional or multi-team projects.
Demonstrated success driving cost/performance improvements or platform reliability gains.
Experience with table formats (Iceberg, Delta, Hudi), query engines (Trino, Druid, Presto), or metadata/catalog systems.
Contributions to open-source or published technical work in data infrastructure.
Operating cloud-scale Spark/streaming fleets with strong observability.
Prior experience mentoring and scaling technical teams.
Benefits
Competitive salary and meaningful equity
Unlimited PTO + quarterly recharge days
Premium health, vision, and dental
Team offsites, deep tech talks, and learning stipends
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