At a Glance
- Tasks: Lead the development of a modern Databricks Lakehouse environment and drive engineering best practices.
- Company: A well-established organisation with a people-first culture and a focus on innovation.
- Benefits: Competitive salary, comprehensive benefits, flexible remote work, and a 35-hour week.
- Why this job: Shape platform strategy and contribute to exciting AI and automation initiatives.
- Qualifications: Strong experience in Azure, Databricks, and DevOps practices.
- Other info: Join a collaborative team that values autonomy and continuous improvement.
The predicted salary is between 80000 - 85000 £ per year.
This is an opportunity to step into a highly influential Data Platform Engineering role where you will shape, optimise and own a modern Databricks Lakehouse environment. You will play a key role in driving engineering best practice, improving automation and enabling scalable data solutions across a growing data function.
The Company
They are a large, well‑established organisation known for combining deep technical expertise with a people‑first culture. With a nationwide presence and a modern approach to flexible working, they invest heavily in technology, innovation and colleague development. Their data function is expanding and plays a central role in supporting transformation, decision‑making and future AI initiatives. You will join a collaborative team that values engineering excellence, autonomy and continuous improvement.
The Role
As Lead Data Platform Engineer, you will:
- Develop and deploy Databricks Lakehouse platform solutions within Azure.
- Build and maintain automation for clusters, tagging, monitoring and platform operations.
- Architect and design end‑to‑end data platform solutions focused on scalability, security and reliability.
- Lead delivery using Databricks, PySpark, Spark SQL and Azure Data Factory.
- Drive DevOps best practices including CI/CD, automated testing and infrastructure as code.
- Collaborate closely with data engineers, ML engineers and wider technical teams to deliver robust platform capabilities.
- Take ownership of key data platform projects and influence engineering direction.
- Provide technical leadership and ensure standards, patterns and best practices are followed.
Your Skills and Experience
You will bring:
- Strong commercial experience in Azure and Databricks, with deep knowledge of Lakehouse architecture.
- Proficiency in PySpark, Python, SQL and Spark SQL.
- Strong DevOps engineering skills including CI/CD, automated testing and deployment pipelines.
- Experience with monitoring, logging and alerting solutions.
- Ability to design, build and optimise cloud platform solutions.
- Stakeholder management skills and confidence working across multiple teams.
- API development experience.
- Azure Data Factory knowledge is beneficial.
What They Offer
- Salary between £80,000 and £85,000 plus bonus.
- Comprehensive benefits package and annual pay review.
- Flexible by choice working environment with remote‑first culture.
- 35‑hour working week promoting genuine work‑life balance.
- Opportunities to shape platform strategy and contribute to future AI and automation initiatives.
How to Apply
If you are a strong Data Platform Engineer with deep Databricks expertise and want to take ownership of a modern Azure Lakehouse environment, please apply today.
Lead Data Platform Engineer in Preston employer: Harnham
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Data Platform Engineer in Preston
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repo showcasing your Databricks and Azure projects. This gives potential employers a taste of what you can do beyond your CV.
✨Tip Number 3
Prepare for interviews by brushing up on common technical questions related to Databricks and Azure. Practise explaining your thought process clearly; it’s all about demonstrating your expertise!
✨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!
We think you need these skills to ace Lead Data Platform Engineer in Preston
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your experience with Azure and Databricks in your application. We want to see how you've used these technologies in real-world scenarios, so don’t hold back on the details!
Tailor Your Application: Take a moment to customise your application for this role. Mention specific projects or experiences that align with the responsibilities of a Lead Data Platform Engineer. This shows us you’re genuinely interested and have done your homework.
Be Clear and Concise: When writing your application, keep it clear and to the point. We appreciate well-structured applications that are easy to read. Use bullet points if necessary to make your key achievements stand out!
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it makes the whole process smoother for everyone involved.
How to prepare for a job interview at Harnham
✨Know Your Databricks Inside Out
Make sure you brush up on your Databricks knowledge before the interview. Be ready to discuss your experience with Lakehouse architecture and how you've implemented it in past projects. This will show that you’re not just familiar with the technology, but that you can also leverage it effectively.
✨Showcase Your DevOps Skills
Since this role heavily involves DevOps practices, prepare to talk about your experience with CI/CD, automated testing, and infrastructure as code. Bring examples of how you've improved automation in previous roles, as this will demonstrate your ability to drive engineering best practices.
✨Prepare for Technical Questions
Expect technical questions around PySpark, SQL, and Azure Data Factory. Practise explaining complex concepts in simple terms, as you may need to communicate these ideas to stakeholders who aren't as technically savvy. This will highlight your communication skills and technical expertise.
✨Emphasise Collaboration and Leadership
This role requires collaboration with various teams, so be prepared to discuss how you've worked with data engineers and ML engineers in the past. Share specific examples of how you've taken ownership of projects and influenced engineering direction, showcasing your leadership abilities.