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

Apply Now

Software Engineer / Data Engineer

Carpata
City of London
2 days ago
Create job alert

Build the Data Infrastructure That Powers the Automotive Industry

Typescript or Python Full-time London

About Us

At Carpata, our vision is to build the vehicle and parts data infrastructure that powers the automation of the entire automotive aftersales industry. We're working with garages, dealerships, manufacturers, parts suppliers, and insurance companies across the ecosystem.

We're looking for a talented, customer-focused engineer who holds exceptionally high standards for accuracy, approaches challenges creatively, and obsesses over automation because automotive data is always evolving.

This is a unique opportunity to join a seed-stage company founded by experienced entrepreneurs who have built and exited automotive tech businesses. Backed by Concept Ventures (Eleven Labs, Jigcar, Superlinked), Nosara Capital (LeafLink, Max Retail), and angels from UK automotive tech leaders like CarWow, JustPark, Autotrader, and Bumper, we have big ambitions to drive change.

We're building a world-class team where you'll solve a huge pain point felt by millions across the globe in a +$2 trillion industry and do the most impactful work of your career. Join us in building the future of B2B parts.

Industry-wide Problems We're SolvingEliminating Manual Parts Procurement

We're eliminating time-consuming part lookups and quote creation for automotive businesses, enabling them to order the right parts, first time, confidently. Service teams will be able to instantly convert customer queries into OEM part numbers, eliminating costly returns and delays.

Workflow Automation

Dealership health checks automatically generate accurate service recommendations, enabling fleet operators to procure parts across hundreds of vehicles without manual cross-referencing. Integration with existing systems will create unified workflows from inspection to ordering.

Democratising Parts Knowledge: Simple, Reliable Access

Complex vehicle specifications and inconsistent supplier data become invisible to end users through a single, authoritative platform that anyone can use reliably. The industry knowledge shortage is addressed by making parts identification simple enough for less experienced staff to achieve professional-level accuracy.

What You’ll Do

You’ll design and build the core systems that power our platform - from parts validation pipelines and data normalisation tools to catalogue infrastructure and supplier integrations. Working closely with our lead engineer, automotive experts and founders, you’ll play a key role in how our platform ingests, resolves, and surfaces complex automotive data. You’ll contribute across the stack where needed but bring a backend or data-engineering mindset to solving messy, high-impact problems. Whether you’re building matching algorithms, automating internal tooling, or shaping our API design, you’ll be helping us turn fragmented data into simple, reliable workflow automation for parts procurement.

What We're Looking ForMust-Haves: The Non-Negotiables

Data Expertise with High Standards

  • Strong experience cleaning and normalising data from multiple sources
  • Obsession with accuracy and data quality. 99% accuracy isn't a target; it's essential
  • Experience resolving conflicts between technically correct but differently structured datasets

Automation Mindset

  • You instinctively build systems that can run without manual intervention
  • Experience designing processes that adapt to changing data sources and formats
  • An iterative mindset that achieves automation through continuous improvement
  • Vision for building systems that continuously learn and improve accuracy through real-world usage

The Right Engineering Approach

  • Run at the Hard Stuff: You volunteer for complex data challenges others avoid because that's where breakthroughs happen
  • Show the Numbers: Every decision backed by evidence, with openly shared opportunities for improvement and clear business justification
  • Build Fast. Learn Loud: Ship the minimum that proves the point, get it in front of real users, then iterate based on what breaks

Technical Foundation

  • Strong programming skills (we work primarily in Python and TypeScript)
  • Experience with database design, schema evolution, and query optimisation
  • Understanding of cloud platforms and scalable infrastructure

Startup DNA

  • You've thrived in environments where you define the approach to unsolved problems
  • You build for the diverse realities of automotive businesses - from independent garages to large dealerships
  • You get genuinely excited when someone proves you wrong because it means you're about to make something better
  • You take ownership of our customer outcomes, not just your outputs

Nice-to-Haves: The Multipliers

  • Experience in automotive, complex B2B domains or industries with high SKU complexity
  • Background with data integration challenges in marketplace or e-commerce platforms
  • Previous experience at a fast-growing startup
  • Demonstrable interest in cars (bonus, but not essential)

This Role Is NOT For You If...

  • You need problems fully defined before starting work
  • You prefer perfecting systems over shipping solutions that customers depend on
  • You think "good enough" is acceptable when our customers demand high accuracy
  • You want to work in isolation rather than as part of a collaborative team where everyone's role matters
  • You're looking for a remote-first working environment
  • You dismiss feedback that challenges assumptions rather than getting excited when proven wrong

Why This Role Will Define Your CareerInfrastructure Impact

Your work will become the foundation that thousands of automotive businesses rely on daily. Every accurate part match, every resolved data conflict, every automated process you build multiplies across the entire industry.

Technical Ownership

You'll have significant influence on our data architecture, methodology, and engineering culture. This isn't a role where someone else makes the technical decisions.

Mission-Driven Culture

Join a team where precision and quality aren't just values - they're how we operate. We're building infrastructure that the entire automotive industry will depend on.

Backed for Scale

With funding from leading investors and industry experts, we have the runway to build transformational infrastructure, not just survive.

Learn from Proven Operators

Work alongside founders with multiple successful exits who understand both the technical and commercial realities of scaling B2B platforms.

£60-85k + up to 1% equity (early employee)

Visa

We cannot sponsor visas at this time

Start

Immediate availability preferred

Hiring Process:

  • Intro call with the CTO about the company, role and your background
  • Technical take-home task
  • Problem-solving session with our Lead Engineer focused on your solution to the take-home task, plus meeting the CEO

Ready to Change the Automotive Industry?

If you're excited about creating the infrastructure that powers an entire industry and building systems that thousands of businesses depend on, we want to hear from you.

Don't wait if you don't tick every box. We're building an inclusive team and value diverse perspectives. If you're energised by running at the hard stuff and have the technical depth to deliver impact, apply now.


#J-18808-Ljbffr

Related Jobs

View all jobs

AI Engineer (data science & software)

Senior Software Engineer - Data Engineering Team

Senior Data Engineer

Senior Data Engineer

Data Engineer - Informatica & Snowflake

Lead Data Engineer

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.

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

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.