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').
Shell Scripting Basics
Practical ability to write and maintain simple shell scripts using Bash and other Unix shells to automate routine system and DevOps tasks. Core skills include variable assignment and substitution, control flow with conditionals such as if and else, looping constructs such as for and while, defining and invoking functions, basic error handling and exit code checks, and logging for observability. Candidates should also be comfortable with basic file and directory operations, invoking and composing commands, and text processing using tools such as grep, sed, and awk. Emphasis is placed on scripting best practices including input validation, defensive programming, clear code organization and readability, making scripts idempotent where appropriate, and handling common edge cases when automating system administration or deployment workflows.
Bash and Shell Scripting
Covers proficiency in writing reliable Bash and POSIX shell scripts to automate common Linux system administration and operational tasks. Topics include shell syntax, variables, parameter expansion, arrays, control flow such as conditionals and loops, functions and modular script design, input and output redirection and pipes, and use of core Unix utilities for text processing such as grep, sed, and awk. Emphasizes defensive and maintainable scripting practices including error handling, exit codes, trap usage, logging, input validation, command substitution, process and job management, debugging techniques, performance considerations, and secure handling of file and process permissions. Typical use cases include service management, backups, log parsing and rotation, user provisioning, monitoring checks, and small operational tooling.
Clean Code and Best Practices
Covers the principles and hands on practices that produce readable, maintainable, and reliable code. Core elements include intent revealing and consistent naming, small focused functions and classes that follow single responsibility, avoiding duplication through refactoring and appropriate abstractions, clear structure and separation of concerns, following language specific idioms and style guides, consistent formatting, concise comments that explain nonobvious intent, defensive programming and robust error handling, edge case handling and input validation, use of linters and static analysis, incremental refactoring techniques, and pragmatic trade offs between ideal design and delivery constraints. Interviewers will also probe involvement in code reviews, version control hygiene, code metrics, and how candidates advocate for and teach coding standards to peers.
Medium Difficulty Coding Problems
Practice and master medium difficulty algorithmic coding problems that commonly appear in technical interviews. Topics include arrays, strings, linked lists, trees, graphs, hash tables, and dynamic programming. Typical techniques to know are two pointer methods, sliding window, breadth first search and depth first search, recursion and backtracking, memoization and bottom up dynamic programming, sorting and greedy heuristics, and common data structure operations. Interviewers evaluate systematic problem solving: clarifying requirements, designing a correct solution, explaining time and space complexity, handling edge cases and input validation, writing clean and working code in your chosen language, and then iterating to optimize performance. Candidates should be comfortable explaining tradeoffs between approaches, testing with example cases, and communicating thought process clearly while coding under time constraints.
Python for DevOps Basics
Basic Python knowledge: syntax, data structures (lists, dictionaries), file I/O, string manipulation, functions, and basic libraries. Ability to write simple utility scripts, not complex applications.