Programming Languages & Core Development Topics
Programming languages, development fundamentals, coding concepts, and core data structures. Includes syntax, algorithms, memory management at a programming level, asynchronous patterns, and concurrency primitives. Also covers core data manipulation concepts like hashing, collections, error handling, and DOM manipulation for web development. Excludes tool-specific proficiency (see 'Tools, Frameworks & Implementation Proficiency').
Programming Fundamentals
Language-agnostic building blocks of writing code: variables, primitive and composite data types, scope and lifetime, functions and callbacks, control flow, and expressions versus statements. Covers the mental model a candidate needs before any language-specific or algorithmic depth. The baseline literacy layer of a technical screen.
Shell Scripting and Automation
Shell-language craft for operations work: Bash and POSIX sh scripting, pipes and redirection, quoting and word splitting, exit codes and set -euo pipefail (including failures inside pipelines), traps and cleanup, argument parsing with getopts, functions and arrays, parameter expansion, here-documents, and text processing with grep, sed, awk and jq, including streaming pipelines over very large log, CSV and JSON Lines files. Also covers writing robust, idempotent, portable scripts (locking, atomic file updates, retries with backoff, safe temp files, GNU versus BSD differences), background jobs and signals, bounded parallelism and SSH fan-out, cron-driven jobs such as log rotation, backups, atomic deploys and health-check watchdogs, secure scripting (eval injection, secrets, path traversal), and debugging, testing and linting shell with ShellCheck and bats. Boundary: general automation design and Python or Go tooling, Linux host administration tasks, observability and alerting design, security detection engineering, and generic algorithmic coding problems are covered elsewhere.
Debugging and Performance Optimization
Finding and fixing what is wrong or slow: systematic debugging strategies, reading stack traces, profiling to locate hotspots, and optimizing execution time and memory. Covers reasoning from symptom to root cause and measuring before optimizing, including runtime, memory, and profiling analysis. Tests how a candidate operates on code they did not write.
Python Programming
Python as an interview language: core syntax, data types and built-in collections, comprehensions, iterators and generators, idiomatic style, and the standard library, extending into data-oriented and automation use of the language and its common libraries. Covers writing correct, Pythonic code and reasoning about the language's semantics. The most heavily exercised language surface in this category across engineering and data roles.