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For Companies At a Glance
- Tasks: Lead and optimise a modern Databricks Lakehouse environment for scalable data solutions.
- Company: Established organisation with a people-first culture and a focus on innovation.
- Benefits: Salary up to £85,000, flexible working, and comprehensive benefits package.
- Why this job: Shape platform strategy and drive AI initiatives in a collaborative team.
- Qualifications: Experience in Azure, Databricks, and strong DevOps skills required.
- Other info: Enjoy a 35-hour work week promoting genuine work-life balance.
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 Leicester employer: Harnham
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Data Platform Engineer in Leicester
✨Tip Number 1
Network like a pro! Reach out to your connections in the data engineering field, especially those who work with Azure and Databricks. A friendly chat can lead to insider info about job openings or even referrals.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Databricks and Azure. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge. Be ready to discuss your experience with CI/CD, automated testing, and cloud solutions. Practice common interview questions related to data platforms to boost your confidence.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive and engaged in their job search.
We think you need these skills to ace Lead Data Platform Engineer in Leicester
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 CV and cover letter for this role. Use keywords from the job description to show us you understand what we're looking for and how you fit into our team.
Be Clear and Concise: When writing your application, keep it straightforward. We appreciate clarity, so make sure your points are easy to read and get straight to the heart of your experience and achievements.
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 this exciting opportunity!
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.
