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For Companies At a Glance
- Tasks: Design and maintain cloud-based data infrastructure using Azure and Databricks.
- Company: Join a leading financial services client focused on innovation.
- Benefits: Hybrid work model, competitive salary, and opportunities for professional growth.
- Why this job: Be at the forefront of data technology and make a real impact.
- Qualifications: 5+ years in Azure services and strong skills in Databricks and Python.
- Other info: Collaborative team environment with excellent career advancement potential.
The predicted salary is between 36000 - 60000 £ per year.
Data Platform Engineer – Permanent
Hybrid (3 days in the office, 2 days WFH)
London
McCabe & Barton are partnering with a leading financial services client to recruit an experienced Data Platform Engineer. This is an excellent opportunity to join a forward-thinking team driving innovation with modern cloud-based data technologies.
Role Overview
As a Data Platform Engineer, you will design, build, and maintain scalable cloud-based data infrastructure using Azure and Databricks. You’ll play a key role in ensuring that data pipelines, architecture, and analytics environments are reliable, performant, and secure.
Key Responsibilities
- Platform Development & Maintenance
- Design and implement data pipelines using Azure Data Factory, Databricks, and related Azure services.
- Build ETL/ELT processes to transform raw data into structured, analytics-ready formats.
- Optimise pipeline performance and ensure high availability of data services.
- Infrastructure & Architecture
- Architect and deploy scalable data lake solutions using Azure Data Lake Storage.
- Implement governance and security measures across the platform.
- Leverage Terraform or similar IaC tools for controlled and reproducible deployments.
- Databricks Development
- Develop and optimise data jobs using PySpark or Scala within Databricks.
- Implement the medallion architecture (bronze, silver, gold layers) and use Delta Lake for reliable data transactions.
- Manage cluster configurations and CI/CD pipelines for Databricks deployments.
- Monitoring & Operations
- Implement monitoring solutions using Azure Monitor, Log Analytics, and Databricks tools.
- Optimise performance, ensure SLAs are met, and establish disaster recovery and backup strategies.
- Collaboration & Documentation
- Partner with data scientists, analysts, and business stakeholders to deliver effective solutions.
- Document technical designs, data flows, and operational procedures for knowledge sharing.
Essential Skills & Experience
- 5+ years of experience with Azure services (Azure Data Factory, ADLS, Azure SQL Database, Synapse Analytics).
- Strong hands-on expertise in Databricks, Delta Lake, and cluster management.
- Proficiency in SQL and Python for pipeline development.
- Familiarity with Git/GitHub and CI/CD practices.
- Understanding of data modelling, data governance, and security principles.
Desirable Skills
- Experience with Terraform or other Infrastructure-as-Code tools.
- Familiarity with Azure DevOps or similar CI/CD platforms.
- Experience with data quality frameworks and testing.
- Azure Data Engineer or Databricks certifications.
Please apply with an updated CV if you align to the key skills required!
Data Platform Engineer in City of London employer: Mccabe & Barton
Contact Detail:
Mccabe & Barton Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Platform Engineer in City of London
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, attend meetups, and engage with professionals on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Azure and Databricks. This gives potential employers a tangible look at what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on common technical questions related to data pipelines and cloud infrastructure. Practise explaining your thought process clearly, as communication is key in collaborative environments.
✨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 take that extra step to connect with us directly.
We think you need these skills to ace Data Platform Engineer in City of London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Azure services and Databricks. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re excited about the Data Platform Engineer role and how you can contribute to our innovative team. Keep it concise but impactful!
Showcase Your Technical Skills: When detailing your experience, focus on your hands-on expertise with tools like Azure Data Factory and PySpark. We love seeing specific examples of how you've built or optimised data pipelines in the past.
Apply Through Our Website: We encourage you to apply directly through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss any important updates from us!
How to prepare for a job interview at Mccabe & Barton
✨Know Your Tech Stack
Make sure you’re well-versed in Azure services, Databricks, and the tools mentioned in the job description. Brush up on your knowledge of data pipelines, ETL processes, and the medallion architecture. Being able to discuss these topics confidently will show that you're ready to hit the ground running.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific challenges you've faced in previous roles and how you overcame them. Use examples that highlight your experience with optimising pipeline performance or implementing security measures. This will demonstrate your ability to think critically and adapt in a fast-paced environment.
✨Collaborate and Communicate
Since the role involves partnering with data scientists and business stakeholders, be ready to talk about your collaboration experiences. Share examples of how you’ve documented technical designs or worked with cross-functional teams. Good communication skills are key in ensuring everyone is on the same page.
✨Ask Insightful Questions
Prepare thoughtful questions about the company’s data strategy, team dynamics, or future projects. This not only shows your interest in the role but also gives you a chance to assess if the company culture aligns with your values. Plus, it can spark a great conversation!
