Database Systems Research Engineer

Our client is a well known technology conglomerate, who are looking for a Database Systems Research Engineer to work on next-generation, high-performance data management technologies.

You’ll combine systems research, software engineering and hands-on prototyping, tackling challenging problems across database architecture, distributed systems, cloud infrastructure and AI data platforms.

What You’ll Work On

• Design and implement database kernels, query optimisers, execution engines, storage engines and indexing systems.
• Develop advanced query processing and optimisation techniques for transactional, analytical and AI workloads.
• Research distributed and cloud-native database architectures, including partitioning, replication and distributed execution.
• Develop storage and data management solutions for structured, multimodal and AI-driven workloads.
• Explore AI data infrastructure including vector search, RAG, knowledge graphs, embeddings and agent memory.
• Profile, benchmark and optimise systems across CPU, memory, storage, networking and accelerators.
• Turn research ideas into high-quality prototypes, technical contributions, patents and publications.

What We’re Looking For

• MSc or PhD in Computer Science, Computer Engineering or a related field.
• Strong background in database systems, distributed systems, operating systems, computer architecture or AI systems.
• Understanding of database internals including query processing, optimisation, storage, indexing and transaction processing.
• Strong programming skills in C, C++, Rust or Go.
• Experience with system design, implementation, benchmarking and performance optimisation.
• Strong problem-solving skills and an interest in open-ended research and engineering challenges.

Nice to Have

• Experience with systems such as PostgreSQL, DuckDB, Spark, Flink, ClickHouse, RocksDB, TiDB or similar.
• Knowledge of NUMA, RDMA, CXL, GPUs, NPUs or heterogeneous computing.
• Experience with vector databases, RAG, knowledge graphs or AI data infrastructure.
• Publications in leading systems/database conferences such as SIGMOD, VLDB, ICDE, EuroSys, OSDI or SOSP.

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