At a Glance
- Tasks: Design and deliver modern data platforms using Databricks for advanced analytics.
- Company: Join a leading tech firm with a focus on innovative data solutions.
- Benefits: Competitive salary, bonus, hybrid working, and career growth opportunities.
- Other info: Interviews next week; apply now for a chance to join a dynamic team.
- Why this job: Shape data strategies and make a real impact in the tech industry.
- Qualifications: 5+ years in Data Architecture and hands-on experience with Databricks.
The predicted salary is between 125000 - 125000 £ per year.
We’re looking for an experienced Data Architect to design and deliver modern, scalable data platforms built on Databricks. You’ll lead the architecture of Lakehouse solutions supporting advanced analytics, AI/ML, and business intelligence, working closely with clients to shape data strategies and deliver real business value. This is a UK‑based role (Edinburgh, Manchester, or London) with hybrid working and occasional client site visits.
Key Details:
- Salary: Up to £125,000 per annum + bonus
- Start Date: ASAP (our client can work around notice periods of up to 3 months)
- Employment type: Permanent
What you’ll do:
- Architect and implement Databricks Lakehouse solutions end‑to‑end
- Design scalable data models and pipelines using Spark, Delta Lake, and PySpark
- Lead client engagements, shaping data strategies and best‑practice architectures
- Win business through presenting solutions and advising potential clients
- Optimise Databricks performance, security, and cost efficiency
- Implement governance, CI/CD, and cloud best practices
What you’ll bring:
- At least 5 years experience in Data Architecture
- 3+ years with Databricks
- End to end pre-sales experience
- Hands‑on data engineering skills (Python, Scala, SQL)
- Experience with Azure
- Solid understanding of data modelling (Kimball, 3NF, Data Vault)
- Excellent stakeholder communication and consulting skills
Databricks certifications highly desirable. Interviews are taking place next week, so if you're interested, please apply today and we’ll be in touch shortly. Alternatively, feel free to reach out to Josh Wolstenholme directly on LinkedIn for a confidential conversation.
Databricks Data Architect employer: Gravitas Recruitment Group (Global) Ltd
Join a forward-thinking company that values innovation and collaboration, offering a dynamic work culture where your expertise as a Data Architect will directly impact client success. With competitive salaries, hybrid working options, and opportunities for professional growth in vibrant cities like Edinburgh, Manchester, or London, you'll thrive in an environment that encourages creativity and continuous learning while delivering cutting-edge data solutions.
Contact Details:
Gravitas Recruitment Group (Global) Ltd Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Databricks Data Architect
✨Tip Number 1
Network like a pro! Reach out to your connections in the data architecture space, especially those who have experience with Databricks. A friendly chat can lead to insider info about job openings or even referrals.
✨Tip Number 2
Show off your skills! Prepare a portfolio or case studies showcasing your previous work with Databricks and data architectures. This will help you stand out during interviews and demonstrate your hands-on experience.
✨Tip Number 3
Practice makes perfect! Get ready for those interviews by rehearsing common questions related to data architecture and Databricks. We recommend doing mock interviews with friends or using online 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’re always on the lookout for talented individuals like you to join our team.
We think you need these skills to ace Databricks Data Architect
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Data Architect role. Highlight your experience with Databricks, data modelling, and any relevant projects you've worked on. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about data architecture and how you can bring value to our team. Don’t forget to mention your hands-on experience with tools like Spark and Azure.
Showcase Your Achievements:When detailing your experience, focus on specific achievements rather than just responsibilities. Did you optimise a data pipeline that saved costs? Share those numbers! We love seeing real impact.
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 makes the process smoother for everyone involved!
How to prepare for a job interview at Gravitas Recruitment Group (Global) Ltd
✨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 solutions, Spark, Delta Lake, and PySpark. Prepare specific examples of how you've implemented these technologies in past projects.
✨Showcase Your Client Engagement Skills
Since this role involves leading client engagements, think about times when you've successfully shaped data strategies for clients. Be prepared to share stories that highlight your consulting skills and how you’ve added real business value through your architectural decisions.
✨Demonstrate Your Data Modelling Expertise
Familiarise yourself with different data modelling techniques like Kimball, 3NF, and Data Vault. Be ready to explain how you've applied these methodologies in your previous roles, as this will show your depth of understanding and practical application.
✨Prepare for Technical Questions
Expect some technical questions related to data architecture, governance, and CI/CD practices. Brush up on your hands-on data engineering skills in Python, Scala, and SQL, and be ready to discuss how you optimise performance, security, and cost efficiency in Databricks.
