Senior Full-Stack Engineer

ComplyCube
London
1 month ago
Applications closed

Related Jobs

View all jobs

Scala Senior Data Engineer

Scala Senior Data Engineer

Scala Senior Data Engineer

Senior Business Support Assistant

Graduate / Senior Geotechnical Engineer

Senior Front End Developer

We’re looking for a Senior Full-Stack Engineer to help evolve our existing web SDKs and compliance platform. Customer engineering teams love our SDKs as they’re easy to integrate and provide their end-users with a simple and seamless verification experience. Our business users love our platform’s simplicity in the complex world of global compliance and identity.

This is a full-time Senior Full-Stack engineering hire on the team. We need someone analytical and technical who enjoys a challenge. We’re a small team and are looking for someone with a great attitude and curiosity who is eager to take ownership of core initiatives and grow with us. If you’re interested in shaping one of the most ambitious companies in our space, join us!

You will:

  • Develop and Evolve Web SDKs: Enhance and maintain the company’s web SDKs to ensure they are easy to integrate and high-performing and deliver seamless verification experiences for end-users.
  • Design, build, and maintain shared components for ComplyCube’s SDKs
  • Work with product managers, user researchers, designers, data scientists, and other engineers to empathize with external users and build solutions to address their needs
  • Optimize consumer flows to create a seamless user experience that delights both businesses and consumers.
  • Lead Technical Initiatives: Take ownership of core technical initiatives, driving the architecture, design, and execution of key features across both frontend and backend systems.
  • Optimize User and Developer Experience: Improve the user-facing platform and the developer experience by creating intuitive, reliable, well-documented SDKs and APIs.

You may be fit for this role if you:

  • 4+ years of coding and design experience in Node JS, React, and MongoDB.
  • Able to write unit tests and achieve good test coverage across the various components.
  • Strong knowledge of version control.
  • Has a passion for building delightful user experiences with a “product first” mindset.
  • Experience in Agile methodologies and tools.

Ready to get started?
Create an account or get in touch.#J-18808-Ljbffr

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Careers

Tips for Staying Inspired: How Data Science Pros Fuel Creativity and Innovation

Data science sits at the dynamic intersection of statistics, computer science, and domain expertise, driving powerful innovations in industries ranging from healthcare to finance, and from retail to robotics. Yet, the daily reality for many data scientists can be a far cry from starry-eyed talk of AI and machine learning transformations. Instead, it often involves endless data wrangling, model tuning, and scrutiny over metrics. Maintaining a sense of creativity in this environment can be an uphill battle. So, how do successful data scientists continue to dream big and innovate, even when dealing with the nitty-gritty of data pipelines, debugging code, or explaining results to stakeholders? Below, we outline ten practical strategies to help data analysts, machine learning engineers, and research scientists stay inspired and push their ideas further. Whether you’re just starting out or looking to reinvigorate a long-standing career, these pointers can help you find fresh sparks of motivation.

Careers

Top 10 Data Science Career Myths Debunked: Key Facts for Aspiring Professionals

Data science has become one of the most sought-after fields in the tech world, promising attractive salaries, cutting-edge projects, and the opportunity to shape decision-making in virtually every industry. From e-commerce recommendation engines to AI-powered medical diagnostics, data scientists are the force behind innovations that drive productivity and improve people’s lives. Yet, despite the demand and glamour often associated with this discipline, data science is also shrouded in misconceptions. Some believe you need a PhD in mathematics or statistics; others assume data science is exclusively about machine learning or coding. At DataScience-Jobs.co.uk, we’ve encountered a wide array of myths that can discourage talented individuals or mislead those exploring a data science career. This article aims to bust the top 10 data science career myths—providing clarity on what data scientists actually do and illuminating the true diversity and inclusiveness of this exciting field. Whether you’re a recent graduate, a professional looking to pivot, or simply curious about data science, read on to discover the reality behind the myths.

Careers

Global vs. Local: Comparing the UK Data Science Job Market to International Landscapes

How to evaluate salaries, opportunities, and work culture in data science across the UK, the US, Europe, and Asia Data science has proven to be more than a passing trend; it is now a foundational pillar of modern decision-making in virtually every industry—from healthcare and finance to retail and entertainment. As the volume of data grows exponentially, organisations urgently need professionals who can transform raw information into actionable insights. This high demand has sparked a wave of new opportunities for data scientists worldwide. In this article, we’ll compare the UK data science job market to those in the United States, Europe, and Asia. We’ll explore hiring trends, salary benchmarks, and cultural nuances to help you decide whether to focus your career locally or consider opportunities overseas or in fully remote roles. Whether you’re a fresh graduate looking for your first data science position, an experienced data professional pivoting from analytics, or a software engineer eager to break into machine learning, understanding the global data science landscape can be a game-changer. By the end of this overview, you’ll be better equipped to navigate the expanding world of data science—knowing which skills and certifications matter most, how salaries differ between regions, and what to expect from distinct work cultures. Let’s dive in.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.