Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Lead Backend Engineer

Ballpark
London
11 months ago
Applications closed

Related Jobs

View all jobs

Data Scientist / Software Engineer

Senior / Lead Data Analyst, Strategic Finance (FP&A)

Data Architect

Statistics & Data Science Innovation Hub Principal Data Scientist

Data Science Manager

Principal Data Scientist

Ballparkis our answer to making research faster, easier and more accessible. The majority of people conducting research in companies aren't researchers - so let's create a platform that meets them where they are.

We want to build the "Canva of research" and create a research platform that is visual, real-time and filled with pre-made templates, questions and tasks so that every team can get deeper insights that lead to better products.

Since our beta launch in 2023, we've added tons of new Enterprise customers like Monzo, Soldo, Guild, Honeybook and Vodafone.

In summer 2023, we raised a seed round from InReach, Haatch, Caffeinated Capital and Bungalow VC who have invested in amazing companies such as Notion, Soldo and Airtable.

Why join Ballpark?

  • We're biased, of course, but we have a super exciting stack that we've built that includes real-time collaboration, video streaming and data processing.
  • A super talented, close-knit engineering team that helped build the system.
  • An amazing list of customers that are highly engaged in improving the platform and constantly providing feedback.
  • The chance to tackle an industry that is ready for change.

The role

As part of this team lead role, you will be primarily responsible for working with the backend team, managing our Python Django backend with a GraphQL API built to power our new Enterprise platform. You will also be required to always think about our product with security in mind. It is essential that you have strong knowledge in operations and backend technologies to maintain and build out our backend infrastructure to be lightning-fast, secure and highly available.

Ballpark's development team focuses on a culture of curiosity, empathy, learning, knowledge and accountability. We believe in owning and delivering what you work on, always making sure that you provide the best experience for our customers and team. As an early-stage startup, you will be given a lot of space to follow your intuition and work with your team to find the best solutions and tools to build a world-class product.

Requirements

Responsibilities

  • Own, deliver and innovate on new product, operations and infrastructure development for all our customers.
  • Ensure that we are the most secure platform in the space by using best practices and aligning us with ISO enterprise standards.
  • Work alongside the product team to define features, in addition to being responsible for deploying, smoke testing and monitoring your own code once reviewed and in the live environment.
  • Co-own and develop projects with your teammates and peers.
  • Participate in thorough, constructive code reviews, ensuring high code quality and providing insightful feedback that improves the code and helps other team members improve their technical skills.
  • Identify issues with technologies or processes and bring solutions to the attention of their team or tech lead.
  • Demo your work regularly to your teammates and the wider company.
  • Be aligned with the company goals and product roadmap, and drive towards them in your sprint work.
  • Be accountable for key performance and product metrics to ensure the product is stable, performant and secure.

Values and Culture of a Team Lead

  • Ability to drive a feature from start to finish, know where each engineer is at, understand whether those engineers are on track, and provide support and leadership to get them back on track if needed.
  • Senior-level technical ability required to understand and unblock the rest of the team.
  • A great mentor who can elevate the skills and performance of the entire team through effective guidance, knowledge sharing, and continuous development opportunities.
  • The ability to translate business needs into technical implementations and craft solutions that are easy to understand and maintain.
  • Strong communication and empathy skills. Be happy to give pragmatic feedback graciously to your team members. Enjoy teaching as much as you enjoy learning.

Technologies we use

These technologies are part of our main stack. If you are familiar with comparable technologies, we'd still be happy to talk.

  • Python 2 (we are in the process of upgrading to python 3)
  • Django backend with GraphQL and Django Rest Framework APIs
  • Celery, RabbitMQ queuing system
  • Redis caching and data storage
  • Google Cloud Platform, Fastly
  • Google Cloud SQL (MySQL)
  • Ansible, Packer & Terraform
  • Linux operating systems and strong command line skills

Nice to have

  • NodeJs - Our realtime backend systems are run on Node using CRDTs and Websockets
  • Docker
  • Data Engineering technologies

Benefits

  • Share options
  • Health and Life insurance
  • ️ Income protection
  • ️ 30 days of holiday
  • ‍ Remote work options (within a couple of hours of the UK timezone)
  • MacBook Pro provided

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

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

Industry Insights

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

Neurodiversity in Data Science Careers: Turning Different Thinking into a Superpower

Data science is all about turning messy, real-world information into decisions, products & insights. It sits at the crossroads of maths, coding, business & communication – which means it needs people who see patterns, ask unusual questions & challenge assumptions. That makes data science a natural fit for many neurodivergent people, including those with ADHD, autism & dyslexia. If you’re neurodivergent & thinking about a data science career, you might have heard comments like “you’re too distracted for complex analysis”, “too literal for stakeholder work” or “too disorganised for large projects”. In reality, the same traits that can make traditional environments difficult often line up beautifully with data science work. This guide is written for data science job seekers in the UK. We’ll explore: What neurodiversity means in a data science context How ADHD, autism & dyslexia strengths map to common data science roles Practical workplace adjustments you can request under UK law How to talk about your neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in data science – & how to turn “different thinking” into a real career advantage.

Data Science Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.