React.js Engineer
Talent Definition

Technical Skills: Essential Expertise
of Our React.js Developers

1. Category #1:

   Tech & Coding

   Within this category, we evaluate essential abilities that significantly impact the caliber and productivity of software creation. Confirming expertise in these aspects ensures our developers can construct sturdy, easily maintained solutions while seamlessly cooperating with colleagues.

   • The engineer with these competencies:

   • Frameworks
     & Libraries

     • Has knowledge of popular frameworks and libraries (e.g. React, Angular, Next.js), their features, and optimal use cases
     • Is aware of new solutions introduced in the world of their chosen tool
     • Knows state management libraries and understands when and which library to use depending on the business requirements of the solution

   • TypeScript
     Knowledge

     • Has a good understanding of TypeScript (e.g., knows and can use advanced typing)
     • Can explain the relationship between TypeScript and JavaScript
     • Can skillfully use existing types and create new advanced types for the solution

   • Design Patterns

     • Consciously uses established practices and patterns
     • Chooses solutions that ensure ease of maintenance for their written code

   • High-Quality
     Code

     • Produces code that is reliable, easy to maintain, reusable, and can be used across different platforms; writes tests that cover various test cases and are independent
     • Knows and applies metrics that demonstrate the good quality of their written code

   • Automated
     Tests

     • Can write automated tests (unit, integration, end-to-end)
     • Can explain the role of different types of tests in the entire testing pyramid
     • Can (in collaboration with other developers and testers) make and justify decisions about the scope of test automation in various contexts (business, technical, human)

   • Git Knowledge

     • Is proficient with the Git version control system
     • Knows various Git workflows and can suggest the selection of one depending on the context (business, technical, human)
     • Can implement the chosen workflow in a project

   • API Knowledge

     • Understands the purpose, functionality, and usage of REST APIs
     • Knows and can explain the differences between REST and GraphQL APIs, as well as the factors that determine which type of API is a better solution in a given case
2. Category #2:

   Problem
   Solving

   Evaluating this category confirms that our developers can devise customized, efficient resolutions and address intricate obstacles. This validation certifies their ability to adapt to evolving technologies and produce high-performing applications in harmony with business goals.

   • The engineer with these competencies:

   • Performance-Focused
     Solutions

     • Knows and applies concepts related to ensuring front-end performance (e.g., network communication, data loading time, resource management, user interactions, layout, animations)
     • Cares about conversion rates, considering application responsiveness on web and mobile platforms
     • Knows and uses tools to improve front-end performance, such as Lighthouse and Google Chrome Tools

   • Adequate
     Solutions

     • Proposes a solution adequate for current business and technical needs
     • Is not limited to one type of solution/architecture/tool (maintains a healthy distance from specific approaches or tools) and knows when to apply an existing solution or create a custom one
     • Identifies the advantages and disadvantages of various solutions/approaches in different contexts (business, technical, human)
     • Can explain the impact and role of non-functional requirements in selecting an appropriate solution

   • Technical
     Problem-Solving

     • Can diagnose an occurring technical problem in a project and propose a solution for that problem

   • Research
     Unknown
     Solutions

     • Can conduct research on an unknown or previously unused solution or tool
     • Can present the advantages, disadvantages, or risks associated with the analyzed solution and suggest a decision regarding its implementation
3. Category #3:

   Infrastructure
   & Deployment

   Appraising this category is vital in confirming that our engineers adeptly administer resources, safeguard applications, and optimize deployment processes. This validation ensures their ability to develop and sustain strong, scalable, and proficient infrastructures for client projects.

   • A competent engineer:

   • Infrastructure
     Management

     • Can identify and apply best practices for deployment, monitoring, debugging, and scalability of a solution deployed in a production environment
     • Knows various front-end libraries and uses them at the appropriate time
     • Can manage dependency updates in the project, knows versioning methods, and tracks vulnerabilities in used libraries for security gaps
     • Can deploy and manage an application in production at a basic level

   • OS & Network
     Concepts

     • Understands basic concepts related to operating systems, network communication, and takes their impact into account when creating frontend solutions

   • Security
     Implementation

     • Is knowledgeable about and can implement good security practices
     • Can practically implement security requirements
     • Understands data encryption methods in web and mobile applications and the tools required for that
     • Has experience in implementing secure authentication methods
     • Knows how to securely store sensitive data in applications, such as user login details and payment information

   • CI/CD
     Deployment

     • Can configure CI/CD pipelines optimally and compatibly with the adopted solution architecture, git workflow, and deployment method on cloud computing resources (or other server resources)
     • Is knowledgeable about tools and services that can help reduce application maintenance costs, such as alternative hosting solutions and open-source libraries
4. Category #4:

   Business
   & Process

   Assessing abilities in this category is crucial for confirming that our engineers can efficiently collaborate with stakeholders, understand project goals, and refine the development procedure. This validation demonstrates their capacity to adjust to client requirements and facilitate a smooth, agile work process.

   • A competent engineer:

   • Business
     Requirements

     • Can identify areas of business requirements that need refinement
     • Can translate business requirements into technical requirements (propose an appropriate solution and plan its implementation)

   • Software
     Development
     Process

     • Understands the software development process using agile methodologies
     • Can report issues related to the current process or methodology being used

Soft Skills: The Human Element
Elevating Our React.js Engineers

1. Category #1:

   Collaboration Skills

   We place great importance on soft skills like efficient communication, exceptional English fluency, a supportive and coaching demeanor, transparency, and a receptiveness to feedback among our team members.

   • The engineer with these competencies:

   • Communication

     • Can communicate noticed problems and proposals for changes in a balanced, neutral, and unbiased way (does not judge, does not elevate themselves, does not ridicule)
     • Can communicate their own needs and problems in the project (especially difficulties encountered), while maintaining a non-entitlement attitude
     • Can participate in discussions in a way that encourages conversation. Can guide the discussion towards making decisions or defining a course of action
     • Can discuss and explain technical issues to non-technical people Category: Soft Skills/Communication

   • English
     proficiency

     • Can use the English language to a sufficient extent to effectively communicate their needs, noticed problems, and ideas
     • Can converse in English on non-technical topics

   • Helpfulness
     & mentoring

     • Is open to supporting other team members in carrying out their tasks (including being open to pair programming)
     • Can mentor less experienced team members (identify areas that need improvement/development, provide knowledge and best practices, check other people’s work and give constructive feedback)

   • Transparency

     • Can admit to a mistake and does not hide its consequences
     • Can admit to not knowing something or lacking experience
     • Does not hide their intentions and goals (if they affect their work in the team/project)
     • Can openly communicate the factors that affect their efficiency and motivation to work

   • Open
     to feedback

     • Understands the broader context of business needs, technical possibilities, and human potential, and their impact on the team’s work style
2. Category #2:

   Work Ethic and Responsibility

   We emphasize qualities like meticulousness, accountability, dedication, efficiency, solid work organization, and adaptability to guarantee that our team members consistently produce top-notch work punctually and can adjust to shifting requirements.

   • The engineer with these competencies:

   • Thoroughness

     • Can thoroughly analyze a technical problem and correctly diagnose its cause
     • Can thoroughly analyze a selected solution, approach, or tool and present the method and chances and risks associated with its implementation

   • Responsibility

     • Feels responsible for the tasks entrusted to them and does not evade responsibility for their actions and their consequences
     • Feels responsible for the solution being created and openly communicates the risks associated with the decisions/actions taken on the solution being created (e.g., its quality, safety, ease of maintenance)

   • Engagement
     & proactivity

     • Can proactively report the need for changes in the solution or the way it is being implemented
     • Openly signals problems and risks in the team/project

   • Effectiveness

     • Can effectively carry out the tasks entrusted to them (by completing them independently or engaging other team members)
     • Openly and without unnecessary delay communicates threats (risks), dependencies, and problems that may prevent them from effectively performing their tasks

   • Good work
     organization

     • Completes assigned tasks and duties within the agreed-upon timeframe, and communicates openly if unable to meet deadlines, especially when other team members’ work depends on it.
     • Can prioritize their tasks while considering the needs of other individuals or the entire team.
     • Respects the time and work hours of other team members when involving them in tasks or projects.

   • Flexibility

     • Can adjust their work style and communication method to the current team’s needs
     • Can adjust the scope of tasks performed to the team’s needs (while being able to communicate if the scope or frequency of changes has a negative impact on their efficiency and motivation to work — see Transparency)

AI Tools Mastery: Boosting Synergy
in Human-AI Partnerships

1. AI Tooling

   Combining AI utilities with the expertise of Code & Pepper’s elite top 1.6% engineers, our Human-AI hybrid teams deliver exceptional, innovative, and reliable FinTech and HealthTech solutions, enriching numerous aspects of the software creation process.

   • The engineer with AI tooling competencies:

   • Code completion and suggestion

     • Knows tools that use AI to analyse code and suggest code snippets, functions, and variables based on the context in which the user is coding (examples include GitHub Copilot and TabNine).

   • Code analysis
     and review

     • Knows tools that use AI to analyse code and provide feedback on code quality, security, and performance (examples include CodeGuru, CodeClimate, and Snyk).

   • Testing and debugging

     • Knows tools that use AI to help developers create tests, find bugs, and debug code (examples include: Applitools, Functionize, and Diffblue Cover).

   • Enhanced
     Security

     • Knows AI-driven security tools that use machine learning to monitor software for potential vulnerabilities and threats (examples include Darktrace and Snyk).