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.
Error Handling and Defensive Programming
Covers designing and implementing defensive, fault tolerant code and system behaviors to prevent and mitigate production failures. Topics include input validation and sanitization, null and missing data handling, overflow and boundary protections, exception handling and propagation patterns, clear error reporting and structured logging for observability, graceful degradation and fallback strategies, retry and backoff policies and idempotency for safe retries. Also address concurrency and synchronization concerns, resource and memory management to avoid exhaustion, security related input checks, and how to document and escalate residual risks. Candidates should discuss pragmatic trade offs between robustness and complexity, show concrete defensive checks and assertions, and describe test strategies for error paths including unit tests and integration tests and how monitoring and operational responses tie into robustness.
Systems Engineering Coding and Problem Solving
Practical coding and algorithmic skills applied to systems and infrastructure tasks. Candidates should demonstrate the ability to write syntactically correct and maintainable code or scripts to automate operations, parse logs, collect metrics, implement health checks, and perform diagnostics; choose appropriate simple data structures and algorithms; reason about time and space complexity at a practical level; apply defensive programming and error handling; debug effectively and write tests to validate behavior; and solve timed technical problems by prioritizing core functionality, correctness, and maintainability. Interviewers commonly use small coding exercises, scripting tasks, or live problems that emphasize operational automation and system oriented problem solving.
Maintainability and Legacy Code
Covers strategies and principles for evolving codebases safely and keeping them easy to understand and change over time. Topics include design principles such as Single Responsibility, Open Closed, Liskov Substitution, Interface Segregation, and Dependency Inversion, removing duplication, establishing appropriate abstraction boundaries, separation of concerns, identifying and remediating code smells, incremental refactoring approaches, regression risk mitigation via tests and feature toggles, backward compatibility and migration strategies, and prioritizing technical debt reduction. Interviewers assess the candidate ability to plan pragmatic refactors, minimize risk during change, and improve long term health of a codebase.
Python Fundamentals for Infrastructure
Core Python programming skills and idioms needed to write reliable infrastructure scripts and small tools. Topics include data types and collections, variables and scope, functions and modular code organization, conditionals and loops, file input and output, string manipulation and formatting, basic use of the standard library for operating system interaction and process control, simple error handling and logging patterns, and working with structured data formats such as JavaScript object notation. Candidates should be able to write clear, readable scripts, explain common language features, and demonstrate how these fundamentals are applied to basic tasks in configuration management, system monitoring, and repetitive administration tasks.
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.
Programming Fundamentals and Code Quality
Encompasses core programming skills, data structures, basic algorithms, language fundamentals, and code quality practices. Expect proficiency with arrays, strings, lists, hash maps or dictionaries, sets, common collection operations, basic sorting and searching algorithms, and tradeoffs between data structures. Understand control flow, functions and modular design, classes and object oriented programming concepts including encapsulation, inheritance, and polymorphism, exception handling, file input and output, and common language idioms for mainstream interview languages such as Python, Java, and C plus plus. Emphasizes writing clean, readable, maintainable code: meaningful naming, modular functions, small interfaces, handling edge cases and errors, logging and documentation, simple testing and debugging strategies, and awareness of time and space complexity for common operations. Candidates should be able to implement correct solutions, follow language specific idioms where appropriate, and demonstrate attention to code quality and readability.
Python for Infrastructure Automation
Use the Python programming language to build automation for infrastructure tasks. Relevant skills include file input and output, parsing and emitting JSON and YAML configuration files, invoking and managing subprocesses, error handling and retries, working with common HTTP and SSH libraries for automation, and processing and transforming infrastructure data structures. Candidates should be able to demonstrate writing reliable scripts and small programs for provisioning, configuration, orchestration, and integrating with automation tooling and APIs.