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').
Network Programming and Scripting Proficiency
Show practical programming and automation skills focused on networking tasks, using languages such as Python, Go, or shell scripting. Topics include socket programming and protocol knowledge for TCP and UDP, HTTP and higher level APIs, automation of network devices and cloud platform APIs, use of client libraries and remote management protocols, writing maintainable scripts and tools with error handling and retries, testing and validation of network code, performance and scaling considerations for scripts and agents, debugging and logging strategies, and code review and collaboration practices for operational tooling. Candidates should be able to discuss examples of network automation, tooling, monitoring integrations, and how they handled reliability and performance trade offs.
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.
Python Fundamentals and Core Syntax
Comprehensive knowledge of core Python language features and syntax, including primitive and composite data types such as integer numbers, floating point numbers, strings, booleans, lists, dictionaries, sets, and tuples. Candidates should understand variable assignment and naming, operators for arithmetic, logical, and comparison operations, and control flow constructs including conditional statements and loops. Expect familiarity with function definition, invocation, parameter passing, return values, and scope rules, as well as common built in functions and idioms such as iteration utilities, list comprehensions, generator expressions, and basic functional utilities like map and filter. Candidates should demonstrate error and exception handling techniques and best practices for writing readable and maintainable code with modularization and clear naming. Practical skills include file input and output, working with common data formats such as comma separated values and JavaScript Object Notation, selecting appropriate data structures with attention to performance and memory characteristics, and applying memory efficient patterns for processing large data sets using iterators and generators. Familiarity with the standard library and common utilities for parsing and transforming data, and the ability to write small code snippets to solve algorithmic and data manipulation tasks, are expected.
Error Handling and Code Quality
Focuses on writing production quality code and scripts that are defensive, maintainable, and fail gracefully. Covers anticipating and handling failures such as exceptions, missing files, network errors, and process exit codes; using language specific constructs for error control for example try except blocks in Python or set minus e patterns in shell scripts; validating inputs; producing clear error messages and logs; and avoiding common pitfalls that lead to silent failures. Also includes code quality best practices such as readable naming and code structure, using standard libraries instead of reinventing functionality, writing testable code and unit tests, and designing for maintainability and observability.
Python Fundamentals and Problem Solving
Comprehensive knowledge of the Python programming language, idiomatic usage, and the ability to implement correct, readable, and testable solutions to coding problems. Core language elements include syntax and semantics, primitive and composite data types such as integers, floats, strings, lists, dictionaries, sets, and tuples, sequence and mapping operations, control flow constructs, functions and closures, and object oriented programming basics including classes, instances, inheritance, and special methods. Additional practical topics include error and exception handling, file input and output operations, comprehensions and generator expressions, generator functions and iteration protocols, context managers, lambda functions, unpacking, and common standard library utilities. Candidates should understand algorithmic time and space complexity for common operations, typical performance characteristics of lists and dictionaries, and common pitfalls such as mutable default arguments and shared mutable state. Interview focused expectations include writing clean correct code without editor assistance, sensible variable naming, implementing basic algorithms and data structure manipulations under time constraints, reasoning about tradeoffs and complexity, and demonstrating testability and code quality.
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.
Python Data Types and Structures
Practical expertise with Python built in data types and collection types and how to use them idiomatically and efficiently. Topics include lists tuples dictionaries sets and related operations append extend pop sort comprehension and slicing, dictionary lookups and set operations, and utilities from the collections module. Candidates should know time and space characteristics of Python operations, how to manipulate these structures for algorithmic solutions, and how to write clear Pythonic implementations that leverage language features for performance and readability.
Scripting and Automation Fundamentals
Practical scripting and basic programming skills used to build and maintain automation across development, testing, operations, and data workflows. Covers core language fundamentals in languages such as Python and shell/bash (variables, control flow, functions, and basic data structures), reading, modifying, and debugging small existing scripts, invoking system commands and working with subprocesses, basic regular expressions and text or log parsing, error handling and troubleshooting approaches, and designing small, repeatable utility scripts that automate repetitive tasks, process output, and support monitoring or reporting. Candidates are expected to write and troubleshoot short scripts and to reason about when automation is worth the investment.