Software Engineer (Java/Kotlin/Scala)

DevITjobs
London
2 months ago
Applications closed

Related Jobs

View all jobs

Software Engineer

Software Engineer

Embedded Software Engineer

Embedded Software Engineer

Azure Software Engineer

Senior Software Engineer (Data Engineering), WAN Insights. (Basé à London)

Social network you want to login/join with:

Software Engineer (Java/Kotlin/Scala), LondonClient:

White Swan Data

Location:

London, United Kingdom

Job Category:

Information Technology

Salary:50,000 - 80,000 GBP per year

EU work permit required:

Yes

Job Description:

Requirements:

  • At least 5 years of commercial software engineering experience.
  • At least 3 years of exposure to modern statically typed application languages such as Scala, Kotlin, Java, C#, F#, Dart, Swift.
  • Python and/or R would be a plus.
  • Strong SQL/RDBMS (such as PostgreSQL or MySQL) experience.
  • Experience deploying and monitoring services on modern cloud platforms, including infrastructure as code and continuous deployment.
  • Experience with asynchronous networking and IO.
  • Exposure to continuous integration and maintaining high coverage test suites.
  • Experience in SOA/RPC frameworks such as gRPC, Thrift, GraphQL and OpenAPI.
  • Very strong attention to detail - our systems should not leak.
  • Software Engineering or Computer Science degree.

Responsibilities:

  • We have experienced rapid growth in the last couple of years and systems which made sense held together by spreadsheets and R scripts are now in need of review and rebuild using RDBMS and application programming languages. So we are hiring a team of software engineers to work alongside our quants and data analysts to build a modern software backend to power our betting analysis and strategies.
  • The system is for in-house use and so is mostly backend, with only as much frontend as necessary to keep the quants happy. You will be working in small teams of around 2-8 including quants and developers, and it’s essentially a greenfield opportunity where you will have a big say in how it gets done. Although we are trying to firm up our stack around Python, Kotlin, PostgreSQL and Google Cloud we are not fanatics (but Kotlin is pretty nice).
  • If you are an ambitious, skilled and maybe just a little bit bored software engineer looking to build a modern system to facilitate data gathering, bet placement, data analysis and systems automation inside a smallish (60 people) company where the CEO is also a developer then this is the role for you!

Technologies:

  • C
  • C#
  • Cloud
  • Dart
  • F#
  • Frontend
  • GraphQL
  • Java
  • Kotlin
  • MySQL
  • Python
  • SQL
  • Scala
  • Swift
  • gRPC
  • API

More:

At White Swan Data we decide what is worth betting on. The technology at the heart of our business produces consistent and significant returns for our clients. We are a small but rapidly growing team of mathematicians, data scientists and software engineers constantly striving to refine our world class betting models while also researching and deploying new ones.

Our work bridges three domains, each challenging in its own right: betting and gambling, quantitative research, and software development. The nature of our work and the relative immaturity of modern betting markets means opportunities to exploit are not in short supply. But people with sufficient skill and versatility to attack these projects are hard to find! So, we are always looking for talented, motivated and organised people.

#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.

Portfolio Projects That Get You Hired for Data Science Jobs (With Real GitHub Examples)

Data science is at the forefront of innovation, enabling organisations to turn vast amounts of data into actionable insights. Whether it’s building predictive models, performing exploratory analyses, or designing end-to-end machine learning solutions, data scientists are in high demand across every sector. But how can you stand out in a crowded job market? Alongside a solid CV, a well-curated data science portfolio often makes the difference between getting an interview and getting overlooked. In this comprehensive guide, we’ll explore: Why a data science portfolio is essential for job seekers. Selecting projects that align with your target data science roles. Real GitHub examples showcasing best practices. Actionable project ideas you can build right now. Best ways to present your projects and ensure recruiters can find them easily. By the end, you’ll be equipped to craft a compelling portfolio that proves your skills in a tangible way. And when you’re ready for your next career move, remember to upload your CV on DataScience-Jobs.co.uk so that your newly showcased work can be discovered by employers looking for exactly what you have to offer.

Data Science Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Data science has become one of the most sought‑after fields in technology, leveraging mathematics, statistics, machine learning, and programming to derive valuable insights from data. Organisations across every sector—finance, healthcare, retail, government—rely on data scientists to build predictive models, understand patterns, and shape strategy with data‑driven decisions. If you’re gearing up for a data science interview, expect a well‑rounded evaluation. Beyond statistics and algorithms, many roles also require data wrangling, visualisation, software engineering, and communication skills. Interviewers want to see if you can slice and dice messy datasets, design experiments, and scale ML models to production. In this guide, we’ll explore 30 real coding & system‑design questions commonly posed in data science interviews. You’ll find challenges ranging from algorithmic coding and statistical puzzle‑solving to the architectural side of building data science platforms in real‑world settings. By practising with these questions, you’ll gain the confidence and clarity needed to stand out among competitive candidates. And if you’re actively seeking data science opportunities in the UK, be sure to visit www.datascience-jobs.co.uk. It’s a comprehensive hub featuring junior, mid‑level, and senior data science vacancies—spanning start‑ups to FTSE 100 companies. Let’s dive into what you need to know.

Negotiating Your Data Science Job Offer: Equity, Bonuses & Perks Explained

Data science has rapidly evolved from a niche specialty to a cornerstone of strategic decision-making in virtually every industry—from finance and healthcare to retail, entertainment, and AI research. As a mid‑senior data scientist, you’re not just running predictive models or generating dashboards; you’re shaping business strategy, product innovation, and customer experiences. This level of influence is why employers are increasingly offering compensation packages that go beyond a baseline salary. Yet, many professionals still tend to focus almost exclusively on base pay when negotiating a new role. This can be a costly oversight. Companies vying for data science talent—especially in the UK, where demand often outstrips supply—routinely offer equity, bonuses, flexible work options, and professional development funds in addition to salary. Recognising these opportunities and effectively negotiating them can have a substantial impact on your total earnings and long-term career satisfaction. This guide explores every facet of negotiating a data science job offer—from understanding equity structures and bonus schemes to weighing crucial perks like remote work and ongoing skill development. By the end, you’ll be well-equipped to secure a holistic package aligned with your market value, your life goals, and the tremendous impact you bring to any organisation.