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For Companies At a Glance
- Tasks: Collaborate to design scalable data models and build generative AI-enabled workflows.
- Company: Rapidly scaling tech startup focused on enterprise data and AI solutions.
- Benefits: Competitive salary, equity, flexible hybrid work, and strong mentorship.
- Why this job: Join a high-growth startup and tackle complex enterprise challenges with cutting-edge technology.
- Qualifications: 2-6 years in data engineering or product-focused engineering; strong Python and SQL skills.
- Other info: Dynamic environment with opportunities for rapid learning and career growth.
The predicted salary is between 36000 - 60000 £ per year.
Location: London (hybrid 3 days onsite)
The Opportunity
We are partnering with a rapidly scaling, venture-backed technology startup building a next-generation enterprise data and AI platform. They are looking for a Product Engineer who thrives at the intersection of product thinking, data engineering, and applied AI. This role is ideal for someone excited about turning real-world complexity into reusable, configurable platform capabilities — enabling enterprise customers to deploy powerful solutions without bespoke engineering every time.
In a world where competitive advantage is driven by adaptable platforms rather than one-off implementations, you will help lay the technical foundations that allow the product to scale across industries, geographies, and operating models.
About the Company
The company is developing a category-defining Strategy & Decision Intelligence platform that unifies internal and external data into a single, intelligent system. It enables large enterprises — including global industrial and Fortune 500 organisations — to make clearer, faster, and more durable strategic decisions. Founded by experienced technology and business leaders, the company launched in the early 2020s and has since seen strong enterprise adoption, significant institutional backing, and rapid growth. Their platform combines deep data integration, enterprise-grade workflows, and cutting-edge generative AI to deliver step-change productivity gains for lean teams.
As the platform scales, success depends on transforming learnings from customer deployments into core, reusable product functionality.
Product Engineering in this environment is about:
- Generalising from complex, real-world use cases
- Designing abstractions that work across diverse enterprise contexts
- Building flexible systems that scale without fragmenting
You will work closely with customer-facing engineers, product leaders, and end users to identify common patterns — then turn them into configurable capabilities within a single, scalable codebase.
What You Will Be Doing
- Collaborate with engineers, product managers, and customers to understand emerging use cases
- Translate those use cases into reusable, configurable platform components
- Design scalable data models, workflows, and abstractions that support high variability
- Build and extend generative AI-enabled workflows as part of the core product
- Develop and maintain robust data pipelines using Python, PySpark, and distributed systems
- Balance near-term delivery with long-term platform maintainability and coherence
- Contribute to architectural decisions shaping the evolution of the platform
What We Are Looking For
- 2–6 years' experience in data engineering, analytics engineering, or product-focused engineering
- Experience building platforms or products, not just one-off solutions
- Strong ability to turn ambiguous business problems into clean technical designs
- Solid foundations in Python, PySpark, and SQL
- Comfortable operating in a fast-moving startup environment
Nice to Have
- Experience with modern data platforms (e.g. Foundry, Databricks, Snowflake, dbt, Airflow)
- TypeScript experience
- API design and backend product development exposure
- Familiarity with enterprise systems (ERP, CRM, etc.)
- Exposure to generative AI systems or AI-enabled workflows
What is On Offer
- Join a category-defining, high-growth startup solving complex enterprise problems
- Work alongside a highly experienced, interdisciplinary leadership team
- Strong mentorship and a steep, rewarding learning curve
- Competitive salary and meaningful equity
- Flexible hybrid working and visa sponsorship where required
- Modern London office designed for collaboration
- A company committed to social and environmental responsibility
Product Engineer in London employer: SR2 | Socially Responsible Recruitment | Certified B CorporationTM
Contact Detail:
SR2 | Socially Responsible Recruitment | Certified B CorporationTM Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Product Engineer in London
✨Tip Number 1
Network like a pro! Reach out to people 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 put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your projects, especially those related to data engineering and AI. This gives you a chance to demonstrate your expertise beyond just a CV.
✨Tip Number 3
Prepare for interviews by practising common questions and scenarios relevant to product engineering. Think about how you can articulate your experience with Python, PySpark, and building scalable systems in a way that resonates with the interviewers.
✨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 exciting projects.
We think you need these skills to ace Product Engineer in London
Some tips for your application 🫡
Show Your Passion for Product Engineering: When writing your application, let us see your enthusiasm for product engineering! Share specific examples of how you've tackled complex problems and turned them into scalable solutions. We love seeing candidates who are genuinely excited about the intersection of data and AI.
Tailor Your Experience: Make sure to highlight your relevant experience in data engineering and product-focused roles. We want to know how your background aligns with our needs, so don’t be shy about showcasing your skills in Python, PySpark, and SQL. Tailoring your application can really make you stand out!
Be Clear and Concise: Keep your application clear and to the point. We appreciate well-structured applications that get straight to the heart of your qualifications. Avoid jargon unless it’s necessary, and remember, clarity is key when discussing your technical designs and experiences.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of your application and ensures you’re considered for the role. Plus, it’s super easy to do, so why not give it a go?
How to prepare for a job interview at SR2 | Socially Responsible Recruitment | Certified B CorporationTM
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description, especially Python, PySpark, and SQL. Brush up on your experience with data platforms like Databricks or Snowflake, as these could come up during technical discussions.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific examples where you've turned complex business problems into clean technical designs. Think about how you can demonstrate your ability to generalise from real-world use cases and create scalable solutions.
✨Understand the Company’s Vision
Familiarise yourself with the company’s mission of building a next-generation AI platform. Be ready to discuss how your skills and experiences align with their goals, particularly in terms of creating reusable, configurable capabilities for enterprise customers.
✨Ask Insightful Questions
Prepare thoughtful questions that show your interest in the role and the company. Inquire about their approach to product engineering, how they handle customer feedback, and what challenges they foresee as the platform scales. This will demonstrate your engagement and strategic thinking.
