At a Glance
- Tasks: Build and scale systems for advertising and data workflows using cutting-edge tech.
- Company: Join a dynamic team focused on innovative solutions in the tech industry.
- Benefits: Enjoy competitive salary, remote work options, and opportunities for professional growth.
- Other info: Great chance to grow across multiple engineering domains in a collaborative environment.
- Why this job: Make a real impact by working on challenging distributed systems and large-scale data workflows.
- Qualifications: 3-5 years in software or data engineering with strong Python and SQL skills.
The predicted salary is between 60000 - 80000 £ per year.
We’re looking for a Software Engineer to build and scale the systems powering our advertising and data workflows. We work with large-scale advertising and attribution datasets, building systems that connect audience intelligence with campaign execution and measurement. This role sits across backend engineering, data engineering, and ML/data infrastructure. You’ll work across APIs, event pipelines, data infrastructure, partner integrations, and internal tooling supporting campaign workflows and ML/data systems. The role is best suited for engineers who enjoy operating across systems rather than staying within a single specialization.
What You’ll Work On
- Backend & Platform Engineering
- Build and maintain backend services, APIs, and internal tooling
- Design asynchronous workflows and distributed processing systems
- Improve observability, reliability, and deployment workflows
- Debug production issues across infrastructure, application, and data layers
- Data Engineering
- Build and maintain scalable ingestion and processing pipelines
- Process high-volume event and attribution datasets across operational systems
- Design reliable data workflows and maintainable data models
- ML Infrastructure & Experimentation
- Support ML systems with reliable training and inference datasets
- Build pipelines supporting experimentation and feature generation
- Collaborate with ML engineers on production integrations and evaluation workflows
- Partner Data & Integrations
- Integrate external APIs, partner platforms, and operational systems
- Build resilient ingestion systems handling retries, quotas, pagination, and evolving schemas
- Support privacy-conscious attribution and partner data workflows
Tech Stack
- Core Technologies
- Python
- SQL
- PostgreSQL
- Snowflake
- Infrastructure & Platform
- GCP or AWS
- CI/CD pipelines
- Infrastructure as code
- Nice to Have
- dbt
- FastAPI or similar backend frameworks
- Kafka, Pub/Sub, or streaming systems
- AdTech, MarTech, or travel-tech systems
- ML data or experimentation systems
What We’re Looking For
- 3–5 years of experience in software engineering, data engineering, or platform engineering
- Strong programming skills, especially in Python
- Solid SQL and data modeling fundamentals
- Experience building production systems in cloud environments
- Understanding of distributed systems, asynchronous workflows, and operational reliability
- Strong ownership mindset and ability to drive work independently
- Strong engineering fundamentals and ability to quickly learn unfamiliar systems, tools, and domains
Nice-to-Have Experience
- High-volume event or analytics systems
- Advertising, attribution, or customer data platforms
- ML data pipelines or experimentation systems
- API-heavy integration platforms
- Comfortable using AI-assisted engineering tools such as Claude Code, Gemini CLI, OpenAI Codex, GitHub Copilot, or similar developer agents as part of day-to-day development workflows
Why Join
- Work on challenging distributed systems and large-scale data workflows
- Build modern platform and data infrastructure with real business impact
- High ownership and opportunity to grow across multiple engineering domains
Software Engineer in London employer: Navigator
Join a forward-thinking company that values innovation and collaboration, offering Software Engineers the chance to work on challenging distributed systems and large-scale data workflows. With a strong emphasis on employee growth, you will have the opportunity to build modern platform and data infrastructure that drives real business impact, all within a supportive remote or hybrid work environment that fosters high ownership and cross-domain learning.
StudySmarter Expert Advice🤫
We think this is how you could land Software Engineer in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to backend services, APIs, or data workflows. This gives you a chance to demonstrate your expertise beyond just a CV.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python and SQL skills. Practice coding challenges and system design questions that reflect the kind of work we do at StudySmarter. The more prepared you are, the more confident you'll feel!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our team and contributing to our mission.
We think you need these skills to ace Software Engineer in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that match the job description. Highlight your experience with Python, SQL, and any relevant cloud environments to show us you’re the right fit for our Software Engineer role.
Craft a Compelling Cover Letter:Use your cover letter to tell us why you’re passionate about working with large-scale data workflows and distributed systems. Share specific examples of your past projects that align with what we do at StudySmarter.
Showcase Your Problem-Solving Skills:In your application, don’t just list your technical skills; demonstrate how you’ve used them to solve real-world problems. We love engineers who can think critically and tackle challenges head-on!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows us you’re keen on joining the StudySmarter team!
How to prepare for a job interview at Navigator
✨Know Your Tech Stack
Make sure you’re familiar with the core technologies mentioned in the job description, especially Python and SQL. Brush up on your knowledge of cloud environments like GCP or AWS, as well as any relevant frameworks like FastAPI. Being able to discuss your experience with these tools will show that you’re ready to hit the ground running.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific examples where you've tackled complex problems, particularly in distributed systems or data workflows. Think about how you’ve debugged production issues or improved system reliability. This will demonstrate your strong ownership mindset and ability to drive work independently.
✨Understand the Role's Scope
This position spans backend engineering, data engineering, and ML infrastructure. Be ready to explain how your experience aligns with these areas. Highlight any projects where you’ve worked across different systems or collaborated with teams on integrations, as this shows versatility and a collaborative spirit.
✨Ask Insightful Questions
Prepare thoughtful questions about the company’s approach to ML systems, data workflows, and the tech stack. This not only shows your interest in the role but also gives you a chance to assess if the company is the right fit for you. Asking about challenges they face can also provide insight into how you can contribute.
