Note: The job is a remote job and is open to candidates in USA. Teradata is a company that empowers organizations with better information through its Autonomous Knowledge Platform. The role of Staff Database Internals Engineer involves building core components of a next-generation parallel compute engine, focusing on database internals and system architecture.
Responsibilities
- Build components across the engine spine: SQL front end (tokenizer, parser, binder), logical/physical plan layer, rule- and cost-based optimizer, and operators (joins, aggregates, sort, scan)
- Build the storage substrate: Arrow in-memory format, slotted-page on-disk format with checksums, buffer pool, and a B-tree or LSM access method
- Implement transactions and recovery: lock/latch management, MVCC/snapshot isolation, WAL/ARIES, checkpoints, and crash recovery
- Add parallelism and distribution along the correct axis — exchange-based parallel execution for query work, consensus/replication/atomic-commit for data correctness — without conflating the two
- Write design specifications before coding (schemas; null/empty/duplicate semantics; memory budget and spill behavior; cost characteristics), write tests first, implement behind the established operator interface, verify safety then speed, and report the benchmark delta
Skills
- Deep expertise in distributed query optimization: cascading optimizers, Abstract Syntax Tree (AST) binding, logical and physical plan distribution
- Experience designing parallel execution pipelines where distribution is a first-class concern, not an afterthought
- Familiarity with systems like Apache DataFusion or similar distributed execution frameworks
- Strong hands-on background with analytical/embedded engines (e.g., DuckDB, DataFusion) and their internals
- Deep knowledge of pipeline execution, vectorized processing, file system I/O, and open table formats (Iceberg, Delta)
- Experience with transaction management, lock managers, cache management, or OS-level scheduling
- Systems programming in Rust or modern C/C++ with memory-safety discipline
- Relational foundations end to end: relational algebra and the algebraic laws behind query rewrites, logical→physical lowering, and cost-based optimization
- Demonstrated depth in at least one area of the engine spine (front end, plan/optimizer, operators, storage engine, transactions/recovery, or scale-out) with working literacy across its neighbors
- Vectorized execution over a columnar (Arrow) representation: batch-at-a-time operators, the pull/iterator model, validity-bitmap-correct null handling, zero-copy buffer sharing
- Cost reasoning at the metal: cache behavior, alignment, SIMD, allocation patterns, false sharing in parallel accumulators
- Test- and benchmark-gated engineering: golden/sqllogictest, property and fuzz testing, deterministic simulation testing for concurrent/distributed paths, and microbenchmarks (Criterion/Google Benchmark) plus a TPC-H subset
- Sophisticated, hands-on use of AI coding agents directed against a reference-grade spec
- Communicates clearly — can describe a system or problem at the right level of abstraction for any audience
- Doer over theorist — moves from concept to working prototype quickly; validates by building
- Intellectually curious and self-directed — digs deep independently before asking for help; brings answers and proposals
- Collaborative with peers — receptive to input and direction while owning your area end-to-end
- Comfortable with evolving requirements — writes design documents to create clarity
- High personal bar for quality
Benefits
- We embrace a flexible work model because we trust our people to make decisions about how, when, and where they work.
- We focus on well-being because we care about our people and their ability to thrive both personally and professionally.
- We are committedto actively workingto foster an inclusive environment that celebrates peoplefor all of who they are.
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