Backend Engineer

Kitman Labs
Manchester
1 month ago
Applications closed

Related Jobs

View all jobs

Backend Engineering Lead

Backend Engineer - Customer Risk Monitoring (MLOps Growth Path)

Data Engineer / Back End Developer - UKIC DV

QA/Test Engineer

Product Engineer

NET Developer

Kitman Labs is a global human performance company, disrupting and transforming the way the sports industry uses data to increase the performance of the world's top athletes.

Driven by a passion to innovate in the areas of sports performance, analytics and user experience, we have assembled a team of the industry’s top data scientists, sports performance scientists, product specialists and engineers. The company received recognition by Fast Company in 2019 as one of the most innovative companies in the world.

Kitman Labs’ advanced Outcome-driven Analytics and Performance Intelligence Platform are used by over 700 teams in 50 leagues on 6 continents spanning soccer, rugby, American football, baseball and ice hockey.

The Role

Backend engineers are responsible for building the core data-flows of Kitman Labs products. They do this with a focus on security, privacy, robustness and performance.

The backend engineering team builds APIs and data processing pipelines that handle massive amounts of data from sports teams all over the globe. In conjunction with our Data Science team, they build and maintain data models which embody the cutting edge of injury risk prevention technology.

We’re looking for people with a strong background or interest in building successful products. You’ll be happy dealing with systems that involve many moving pieces. New technologies or approaches to solving problems don’t bother you. You are detail-oriented but also pragmatic and considered in where you spend time and effort.

We will expect you to

  • Design, build, and maintain APIs, services and data-stores.
  • Constantly improve our engineering processes, standards and tooling.
  • Work with our frontend engineers to build features that users love to use.
  • Help our data scientists to research and implement the latest data processing techniques and models.
  • Debug production issues across services and multiple levels of the stack.
  • Contribute to our technical architecture as we grow.

Experience and skills we look for

  • Experience building APIs or as part of a team building dynamic web applications.
  • Shown an ability to take on new technologies and languages.
  • We work mostly in Ruby but this isn’t a prerequisite; we’re more interested in your ability to learn.
  • Hold yourself and others to a high bar.
  • Take pride in working on projects through to a successful completion.
  • Recognise the value of standardised, fully tested code that is delivered in a CI/CD environment.

We heavily utilise Amazon Web Services, so experience with AWS or similar is a bonus.

Our platforms are orchestrated using Terraform, and some familiarity with infrastructure as code as a pattern is an advantage.

Benefits

At Kitman Labs, we pride ourselves on being the best and working with the best, so it should be no surprise that we are also dedicated to keeping the best through building a world-class work culture.

We truly believe that a successful company begins through having an outstanding and inspiring culture, so our benefits reflect this:

  • Competitive salary
  • Health insurance for employee & dependants
  • Meaningful equity
  • Pension Plan
  • Life Cover
  • Income protection
  • Wellbeing benefits

Location

While this role allows for remote work, occasional face-to-face gatherings are recommended.

Diversity

In addition to building a team with diverse skill-sets, Kitman Labs is committed to hiring people with diverse backgrounds. We do not discriminate based on age, civil or family status, disability, ethnicity, gender, race, religion, or sexual orientation. If you are a person with a disability and require assistance during the application process, please let us know.

You can find information about how we process, share and keep your personal data safe by reading ourprivacy policy.

#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.

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.

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.

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.