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- Tasks: Lead data engineering projects using Azure Databricks and GenAI technologies.
- Company: Join a forward-thinking tech company focused on innovation and collaboration.
- Benefits: Enjoy remote work, competitive salary, and opportunities for professional growth.
- Other info: Dynamic role with mentorship opportunities and a focus on best practices.
- Why this job: Make an impact by building cutting-edge data platforms that drive analytics and AI.
- Qualifications: 8+ years in data engineering with strong Azure Databricks and Python skills.
The predicted salary is between 70000 - 90000 £ per year.
Location: UK Remote
Engagement: Permanent
Overview: We are seeking a Senior Azure Data Engineer to take ownership of the data engineering capability across multiple enterprise-scale Azure Databricks programmes. This role sits at the intersection of data engineering, cloud architecture, and GenAI enablement, building production-grade lakehouse platforms that power analytics, automation, and AI-driven applications. You will act as a technical lead and client-facing engineer, responsible for designing, delivering, and governing scalable Azure + Databricks data platforms.
Key Responsibilities:
- Architecture Leadership
- Define Azure Databricks lakehouse architectures (medallion model)
- Review and approve engineering designs across projects
- Data Engineering Delivery
- Build end-to-end pipelines using: Azure Databricks (PySpark, Delta Lake, Workflows), Azure Data Factory / Synapse Pipelines, ADLS Gen2
- Deliver curated data products (bronze / silver / gold)
- GenAI Enablement
- Prepare data for RAG and AI workloads
- Work with Azure OpenAI + Azure AI Search
- Implement embedding, chunking, and retrieval strategies
- CI/CD & Infrastructure
- Implement IaC using Terraform or Bicep
- Manage CI/CD pipelines using Azure DevOps or GitHub Actions
- Use Databricks Asset Bundles for deployment automation
- Governance & Security
- Implement Unity Catalog, Purview, RBAC, and data lineage
- Ensure secure-by-design architecture (Key Vault, Entra ID)
- Client Engagement
- Lead workshops, design sessions, and technical discussions
- Translate business requirements into structured engineering delivery
- Mentorship
- Guide and support mid-level engineers
- Enforce engineering standards and best practices
Required Experience:
- 8+ years in data engineering
- 4+ years hands-on Azure data platform experience
- Expert-level Azure Databricks (PySpark, Delta Lake, Jobs, tuning)
- Strong Azure Data Factory / ADLS Gen2 / Azure SQL experience
- Solid Python and SQL engineering background
- Experience with lakehouse / medallion architecture
- CI/CD & IaC (Terraform or Bicep + Azure DevOps/GitHub Actions)
- Understanding of Azure AI Search / Azure OpenAI / RAG concepts
- Experience with Unity Catalog / Purview / data governance frameworks
Soft Skills:
- Strong client-facing communication skills
- Confident leading technical design discussions
- Ability to manage ambiguity and define structure
- Mentoring and leadership capability
Nice to Have:
- Power BI / Fabric experience
- Salesforce data integration experience
- Microsoft certifications (DP-203, DP-700, AZ-305, etc.)
- Experience in real-time or operational data environments
- Exposure to Data/AI Centre of Excellence environments
Senior Azure Data Engineer (Databricks + GenAI) employer: TECHNOLOGY AND RISK RECRUITMENT LTD
Contact Detail:
TECHNOLOGY AND RISK RECRUITMENT LTD Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Azure Data Engineer (Databricks + GenAI)
✨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. Attend meetups or webinars to get your name out there and learn about potential job openings.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Azure Databricks and GenAI. This will give you an edge during interviews and help demonstrate your hands-on experience.
✨Tip Number 3
Prepare for technical interviews by brushing up on key concepts like lakehouse architecture and CI/CD practices. We recommend doing mock interviews with friends or using online platforms to get comfortable with the format.
✨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 about their job search!
We think you need these skills to ace Senior Azure Data Engineer (Databricks + GenAI)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the Senior Azure Data Engineer role. Highlight your expertise in Azure Databricks, data engineering, and any relevant projects you've led. We want to see how you fit into our vision!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to tell us why you're passionate about data engineering and how your experience aligns with our needs. Be sure to mention your client engagement skills and any leadership roles you've taken on.
Showcase Your Projects: If you've worked on any impressive data engineering projects, don't hold back! Include links or descriptions of your work with Azure Databricks, CI/CD pipelines, or GenAI enablement. We love seeing real-world applications of your skills.
Apply Through Our Website: We encourage you to apply directly through our website for the best chance of getting noticed. It helps us keep track of your application and ensures you’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at TECHNOLOGY AND RISK RECRUITMENT LTD
✨Know Your Tech Inside Out
Make sure you’re well-versed in Azure Databricks, PySpark, and Delta Lake. Brush up on your knowledge of building end-to-end data pipelines and be ready to discuss specific projects where you've implemented these technologies.
✨Showcase Your Leadership Skills
As a Senior Azure Data Engineer, you'll need to demonstrate your ability to lead technical discussions and workshops. Prepare examples of how you've guided teams or mentored mid-level engineers in the past.
✨Prepare for Client Engagement Scenarios
Expect questions about translating business requirements into technical solutions. Think of instances where you've successfully engaged with clients and how you’ve navigated their needs into structured engineering delivery.
✨Understand Governance and Security
Familiarise yourself with Unity Catalog, Purview, and secure-by-design architecture principles. Be ready to discuss how you’ve implemented governance frameworks in previous roles and why they matter in data engineering.