At a Glance
- Tasks: Lead the design and build of scalable, cloud-native data solutions.
- Company: Join a global leader in personalised photo products with a focus on innovation.
- Benefits: Enjoy a competitive salary, bonus, and a flexible work environment.
- Other info: Opportunity to mentor engineers and influence cross-functional teams.
- Why this job: Shape the future of data systems in a people-first, purpose-driven culture.
- Qualifications: Strong background in software and data engineering; proficient in Python and SQL.
The predicted salary is between 72000 - 84000 £ per year.
Salary: £100,000 + 15% Bonus
Location: Central London, 2 days in office
We’re hiring on behalf of our client, a global leader in personalized photo products, for an experienced Principal Data Engineer to join their UK data & ML team. This is a senior hands-on leadership role driving data platform strategy and engineering standards as they evolve toward de-centralised data and ML adoption.
Role overview:
You’ll play a central role in re-architecting and scaling their data platform to meet growing business and customer needs. This includes building robust, observable data pipelines, ensuring data trustworthiness, and mentoring a team of engineers while collaborating closely with Product, Ops, and Marketing stakeholders.
Key responsibilities:
- Lead design and build of scalable, cloud-native data solutions with best-in-class governance and observability
- Define technical principles and data engineering standards across distributed teams
- Coach data and analytics engineers on SDLC best practices (CI/CD, testing, versioning)
- Contribute to strategic planning and technical roadmaps in collaboration with product and engineering leads
- Influence cross-functional stakeholders on architecture and implementation trade-offs
- Ensure data is reliable, timely, and actionable for operational and ML-driven use cases
About you:
- Strong background in software and data engineering leadership
- Proficient in Python, SQL, and modern ELT practices (e.g. dbt, Fivetran, Airflow)
- Deep knowledge of data warehousing (Snowflake), AWS services (e.g. Lambda, Kinesis, S3), and IaC (Terraform)
- Experienced in building data platforms with a focus on governance, reliability, and business value
- Comfortable driving architectural conversations and mentoring engineers across disciplines
- Advocate for decentralised data models, such as data mesh
Nice to have:
- Experience with data quality tools (e.g., Monte Carlo)
- Knowledge of data security and compliance
- Previous work in e-commerce or consumer tech
This is a chance to shape the next generation of data systems powering personalised customer experiences at scale - while working in a people-first, purpose-driven culture.
Lead Data Engineer in London employer: Harnham
Join a dynamic and forward-thinking B2B company that prioritises data-driven decision making and offers a fully remote work environment across the UK. With a strong focus on employee growth, you will have the opportunity to lead a talented team while shaping the marketing analytics strategy in a rapidly expanding organisation. Enjoy a collaborative work culture that values innovation and provides significant investment in your professional development.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Data Engineer in London
✨Tip Number 1
Familiarise yourself with the latest trends in data engineering, especially around decentralised data models like data mesh. This knowledge will not only help you in interviews but also demonstrate your commitment to staying ahead in the field.
✨Tip Number 2
Network with professionals in the data engineering space, particularly those who have experience with cloud-native solutions and tools like Snowflake and AWS. Engaging in discussions or attending meetups can provide insights and potentially lead to referrals.
✨Tip Number 3
Prepare to discuss your leadership style and experiences in mentoring engineers. Be ready to share specific examples of how you've influenced architectural decisions and improved team practices in previous roles.
✨Tip Number 4
Research the company’s products and their approach to personalised customer experiences. Understanding their business model will allow you to tailor your conversations and show how your skills can directly contribute to their goals.
We think you need these skills to ace Lead Data Engineer in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights relevant experience in data engineering, particularly with technologies mentioned in the job description like Python, SQL, and AWS services. Use specific examples to demonstrate your leadership skills and technical expertise.
Craft a Compelling Cover Letter:In your cover letter, express your passion for data engineering and how your background aligns with the company's goals. Mention your experience with decentralised data models and your ability to mentor engineers, as these are key aspects of the role.
Showcase Your Projects:If you have worked on relevant projects, consider including a portfolio or a brief summary of these projects in your application. Highlight any experience with building scalable data platforms and your approach to ensuring data reliability and governance.
Proofread Your Application:Before submitting, carefully proofread your application materials. Look for any spelling or grammatical errors, and ensure that your documents are well-structured and easy to read. A polished application reflects your attention to detail.
How to prepare for a job interview at Harnham
✨Showcase Your Technical Expertise
Be prepared to discuss your experience with Python, SQL, and modern ELT practices. Highlight specific projects where you've implemented these technologies, especially in building scalable data solutions.
✨Demonstrate Leadership Skills
Since this is a senior role, be ready to share examples of how you've led teams and mentored engineers. Discuss your approach to coaching on SDLC best practices and how you've influenced architectural decisions.
✨Understand the Business Context
Familiarise yourself with the company's focus on personalised photo products. Be ready to discuss how your data engineering strategies can drive business value and improve customer experiences.
✨Prepare for Cross-Functional Collaboration
Expect questions about how you would work with Product, Ops, and Marketing teams. Think of examples where you've successfully collaborated across disciplines to achieve common goals.
