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For Companies At a Glance
- Tasks: Build innovative products at the intersection of data engineering and AI workflows.
- Company: Fast-growing tech company revolutionising enterprise data and AI platforms.
- Benefits: Competitive salary, equity, hybrid work, and growth opportunities.
- Why this job: Shape a core platform and work on real-world AI applications.
- Qualifications: 2-6 years in data or product-focused engineering with Python and SQL skills.
- Other info: Dynamic startup environment with evolving priorities and learning opportunities.
The predicted salary is between 55000 - 70000 £ per year.
Location: London (Hybrid – 3 days onsite)
Level: Mid–Senior (roughly 2–6 years' experience)
The Opportunity
We're working with a fast-growing, venture-backed technology company building an enterprise data and AI platform used by large, global organisations. They're hiring a Product Engineer — someone who enjoys building real products, not just pipelines or one-off solutions. This role sits at the intersection of data engineering, backend engineering, and product thinking, with exposure to modern AI-enabled workflows.
You'll work on problems where customer needs are complex and messy — and your job is to turn those needs into reusable, configurable platform features that can be deployed again and again. If you like understanding why something is being built, not just what, this role is likely a strong fit.
What You'll Be Doing (Day to Day)
- Work closely with product managers, engineers, and end users to understand new customer use cases
- Turn those use cases into reusable platform capabilities, rather than bespoke solutions
- Design and build scalable data models, workflows, and abstractions that work across multiple customers
- Build and extend AI-enabled workflows as part of the core product (e.g. decision support, automation, insight generation)
- Develop and maintain data pipelines using Python, PySpark, SQL, and distributed systems
- Make pragmatic engineering decisions that balance short-term delivery with long-term product quality
- Contribute to technical and architectural discussions as the platform evolves
You won't be expected to "know everything" on day one — learning and iteration are part of the role.
What They're Looking For
- 2–6 years' experience in data engineering, analytics engineering, or product-focused engineering
- Experience working on products or platforms, not just isolated projects
- Confidence turning loosely defined business problems into clean technical solutions
- Solid foundations in Python, SQL, and working with large datasets
- Comfortable in a startup environment where priorities evolve and things aren't always fully specified
Nice to Have (Not Essential)
- Experience with modern data platforms (e.g. Databricks, Snowflake, dbt, Airflow, Foundry)
- Some exposure to backend development or API design
- TypeScript experience
- Familiarity with enterprise systems (ERP, CRM, etc.)
- Exposure to AI-enabled systems, generative AI, or workflow orchestration
If you don't tick all of these boxes, that's absolutely fine.
Why This Role Is Interesting
- You'll help shape a core enterprise platform, not just implement requirements
- Strong exposure to real-world AI applications, not demos or experiments
- Work closely with experienced product and engineering leaders
- Clear opportunity to grow into a senior product-focused engineering role
- Competitive salary, meaningful equity, and hybrid working
If interested, please apply and I'll give you a call.
Product Engineer in England 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 England
✨Tip Number 1
Network like a pro! Reach out to people in your industry on LinkedIn or at meetups. We all know that sometimes it’s not just what you know, but who you know that can help you land that Product Engineer role.
✨Tip Number 2
Prepare for those interviews by practising common questions and scenarios related to data engineering and product thinking. We recommend doing mock interviews with friends or using online platforms to get comfortable with the format.
✨Tip Number 3
Showcase your projects! Whether it's through a portfolio or GitHub, we want to see how you've tackled complex problems and built real products. This is your chance to shine and demonstrate your skills in Python, SQL, and AI workflows.
✨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, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Product Engineer in England
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Product Engineer role. Highlight your experience in data engineering, backend engineering, and any exposure to AI workflows. We want to see how you can turn complex customer needs into clean technical solutions!
Craft a Compelling Cover Letter: Your cover letter is your chance to show us your personality and passion for the role. Explain why you're excited about building real products and how your background makes you a great fit. Don’t forget to mention any relevant projects or experiences that showcase your problem-solving skills!
Showcase Your Technical Skills: Since this role involves working with Python, SQL, and large datasets, make sure to highlight your proficiency in these areas. If you've worked with modern data platforms or AI systems, give us the details! We love seeing practical examples of your work.
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 gives you a chance to explore more about our company culture and values!
How to prepare for a job interview at SR2 | Socially Responsible Recruitment | Certified B CorporationTM
✨Understand the Product Landscape
Before your interview, take some time to research the company’s product and its features. Familiarise yourself with how their platform addresses complex customer needs and think about how you can contribute to building scalable data models and workflows.
✨Showcase Your Problem-Solving Skills
Be prepared to discuss specific examples where you've turned loosely defined business problems into clean technical solutions. Highlight your experience in data engineering and how you've built reusable capabilities rather than bespoke solutions.
✨Brush Up on Technical Skills
Make sure you're comfortable discussing Python, SQL, and any relevant tools like PySpark or modern data platforms. You might be asked to solve a technical problem on the spot, so practice coding challenges that reflect the skills required for the role.
✨Embrace the Startup Mindset
Since the company operates in a fast-paced environment, demonstrate your adaptability and willingness to learn. Share experiences where you've thrived in changing priorities and how you approach making pragmatic engineering decisions.
