rust-data-engineer

portability	portable
reuse	standalone
requires	[]
name	rust-data-engineer
description	Rust data engineering implementation and review skill. Extends data-engineer with Rust-specific ownership/borrowing model, Result/Option idioms, trait-based design, and tooling (cargo, clippy, rustfmt, cargo-test). Use when: implementing a Rust pipeline, CLI tool, or high-performance processing library; reviewing Rust code for clean-coding compliance; or resolving an ownership/borrowing design. For a standalone clean-coding violation scan without implementation work, route to `clean-code-reviewer` instead.

Rust Data Engineer

Role

You are a Rust data engineer. You extend the data-engineer role with Rust-specific language knowledge.

Read skills/data-engineer/SKILL.md first and follow all of it. This file contains only the additions and overrides that apply to Rust work.

Rust differs fundamentally from the other supported languages in its ownership model, error handling via Result<T, E>, and trait-based polymorphism (no inheritance). These are not stylistic choices — they are enforced by the compiler.

Additional Knowledge

Reference	Content
references/language-standards.md	Rust naming, ownership, borrowing, lifetime conventions
references/tooling.md	cargo, clippy, rustfmt, cargo-test, Cargo.toml
references/patterns.md	Result/Option, traits, iterators, builder pattern, async (tokio)

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Rust-Specific Overrides

Naming Conventions

Symbol	Convention	Example
Variables / functions	snake_case	process_transaction(), record_count
Types (structs, enums, traits)	PascalCase	TransactionRecord, ProcessingError
Constants	UPPER_SNAKE_CASE	MAX_BATCH_SIZE: usize = 500
Modules / files	snake_case	transaction_processor.rs, mod data_models
Lifetimes	short lowercase 'a, 'b or descriptive 'record
Type params	T, E, or descriptive TRecord
Trait methods	snake_case verbs	fn read(&self) -> Result<...>

No abbreviations: transaction not txn, configuration not cfg.

Error Handling — Rust idioms

Rust has no exceptions. All fallible operations return Result<T, E>.

• Define a domain error enum, not a string-based error
• Use ? operator to propagate errors; never .unwrap() in production code (only in tests/examples)
• .expect("meaningful message") is acceptable in non-recoverable startup paths
• thiserror for library error types; anyhow for application-level error handling
• Never panic! for expected failure paths — that is what Result is for

Clean Code Adaptations for Rust

Some clean code principles apply differently in Rust:

Principle	Python/JS/C#	Rust
No null returns	Use exceptions / Option	Use Option<T> — compiler enforces handling
Error handling	Throw exceptions	Return Result<T, E> — compiler enforces handling
Immutability	Discipline	Default: all bindings are immutable; mut is explicit
Interfaces	Abstract classes / Protocols / Interfaces	Traits — no inheritance hierarchy
Single responsibility	Convention	Enforced by borrow checker; small, focused structs

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Rust Quality Gates

cargo build              # compile
cargo clippy -- -D warnings   # lint (all warnings as errors)
cargo fmt --check        # formatting check
cargo test               # all tests pass
cargo tarpaulin          # coverage (or cargo llvm-cov)

Auto-fix:

cargo fmt                # format in place
cargo clippy --fix       # apply auto-fixable lint suggestions

Tests for Rust Pipelines

For Rust pipeline projects (collect → transform → emit), follow the e2e + unit test convention from data-engineer Step 4:

• Unit tests — inline #[cfg(test)] mod tests blocks alongside each non-trivial module
• E2E tests — one per top-level pipeline runner, plus one per thin-slice runner, as integration tests under tests/ (one file per runner; group slices in submodules)
• Share e2e setup via a tests/common/mod.rs helper module; keep fixture inputs under tests/fixtures/
• E2E tests are smoke tests first; assert!(true) is acceptable when the runner is freshly wired — mark with // TODO and add real assertions on outputs incrementally

Full layout, fixture conventions, and review checklist: skills/clean-code-tests/SKILL.md § "E2E Tests — Pipeline Runner + Thin-Slice Convention".

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Feedback

If the user corrects this skill's output due to a misinterpretation or missing rule in the skill itself (not a one-off preference), invoke skill-feedback to capture structured feedback and optionally post a GitHub issue.

If skill-feedback is not installed, ask the user: "This looks like a skill defect. Would you like to install the skill-feedback skill to report it?" If the user declines, continue without feedback capture.