Full Stack Software Engineer - Smartly

Datacom

3d•Hybrid

About The Position

Smartly, a Datacom company, is seeking a Full Stack Engineer to work on their Smartly Payroll System. Smartly is a SaaS Online Payroll Product used by over 20,000 clients. The company is a fast-growing FinTech expanding into adjacent markets, offering a fast-paced, fun work environment with opportunities for personal and professional development. The ideal candidate will have at least 2 years of experience in both front-end and back-end development, strong problem-solving skills, the ability to write clean code, and experience mentoring junior engineers.

Requirements

2+ years’ experience working on IT projects across multiple phases of the SDLC.
Recent C# .NET experience with at least 2 years of .NET development.
Experience with web front-end technologies, including HTML, JavaScript, CSS, React, or ASP.NET Razor.
Good understanding of software architecture, design patterns, SOLID principles, and object-oriented programming.
Knowledge of software configuration management using tools such as Git.
Familiarity with service-oriented frameworks.
Ability to implement features, unit tests, and fix complex bugs.
Excellent communication skills, with a strong focus on helping create cohesive, collaborative, and productive teams.
Strong problem-solving and conceptual thinking skills.

Nice To Haves

Public cloud exposure (Azure) is a bonus.

Responsibilities

Owning the day-to-day delivery of assigned work, including clarifying feature-level ambiguity, managing tasks effectively, supporting release, and verifying outcomes in production.
Contributing to team-owned delivery by giving realistic input into effort, raising risks or blockers early, communicating progress clearly, and helping the team deliver work predictably.
Contributing to team-owned quality through appropriate testing, code review participation, safe change practices, and disciplined attention to correctness, maintainability, security, and performance.
Using modern tooling, automation, and AI-assisted development in a practical and controlled way to improve delivery efficiency, feedback loops, and code quality while remaining accountable for the output.
Supporting less experienced engineers through constructive collaboration, review feedback, and strong day-to-day engineering practice.