Software Engineer III, Database Internals, AlloyDB

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.

• 2 years of experience with software development in C or C++.

• 2 years of experience designing, building, or maintaining backend infrastructure, distributed systems, or large-scale storage architecture.

• Experience developing concurrent, multithreaded systems, or engineering core database internals (e.g., storage engines, transaction processing, indexing).

• Experience building fault-tolerant distributed systems, data replication mechanisms, or consensus protocols (e.g., Paxos, Raft).

Preferred qualifications:

• Master's degree or PhD in Computer Science or related technical fields.

• Experience modifying or contributing to the internals of open-source databases (e.g., PostgreSQL, MySQL) or storage engines (e.g., RocksDB, LevelDB).

• Experience with query processing, cost-based query optimization, compiler theory, or vectorized execution engines.

• Experience engineering lock-free data structures, latches, and advanced thread synchronization mechanisms.

• Experience analyzing and tuning system performance using standard benchmarks (e.g., TPC-C, TPC-H) and low-level profiling tools (e.g., perf, eBPF).

About the job:

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.

The AlloyDB team is part of Google Cloud Databases. Our mission is to build a relational database for the cloud era. We are re-imagining the traditional Relational Database Management System (RDBMS) architecture by disaggregating compute and storage, allowing for independent scaling and availability.

In this role, you will work on the core database engine. You will design and implement features deep within the stack—ranging from the Query Optimizer and Execution Engine to the Storage Layer and Transaction Manager. You will collaborate with engineering leadership to push the boundaries of what a relational database can do in the cloud.

Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $147000 - $210000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google. Responsibilities:

• Design and implement high-performance C++ components for the AlloyDB kernel, focusing on critical areas such as storage engines, indexing, buffer management, and transaction logging.

• Build and harden distributed consensus and replication mechanisms to ensure data consistency, high availability, and zero data loss during failovers across large-scale deployments.

• Integrate upstream PostgreSQL features into a custom, cloud-native storage engine, ensuring full SQL compliance while maximizing the advantages of Google’s underlying hardware and infrastructure.

• Profile and optimize the core database path to reduce latency, improve concurrency, and optimize query execution plans for demanding, enterprise-scale workloads.

• Collaborate with cross-functional teams to resolve architectural challenges and performance bottlenecks across a fleet of databases.