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- Tasks: Design and build scalable data pipelines using Python and PySpark.
- Company: Join a dynamic team focused on innovative data solutions in Azure.
- Benefits: Competitive daily rate, remote work, and opportunities for professional growth.
- Why this job: Make an impact by developing production-grade data platforms with cutting-edge technology.
- Qualifications: Strong Python skills, experience with PySpark, and a passion for clean code.
- Other info: Collaborative environment with a focus on continuous delivery and improvement.
The predicted salary is between 72000 - 108000 £ per year.
We are seeking a highly capable Python-focused Data Engineer to join a delivery-driven team building and supporting complex data platforms in Azure. This role is heavily weighted towards Python software engineering rather than traditional ETL-only work. The successful candidate will be someone who writes clean, maintainable, and well-tested Python code, and is comfortable treating data pipelines as production-grade software.
A significant portion of the work involves designing and maintaining complex, test-driven Python data flows, with PySpark used as the execution engine rather than the primary focus. Strong Python fundamentals, testing discipline, and code quality are critical to success in this role.
What you'll be doing:
- Designing and building scalable data pipelines with a Python-first approach
- Developing complex data flows with a strong emphasis on clean architecture, reusable Python modules, and testability
- Writing comprehensive unit tests and BDD tests (Behave), including mocking and patching
- Using PySpark to process large-scale datasets while keeping business logic in Python
- Creating, maintaining, and optimising Delta Lake tables for performance and reliability
- Building and running applications in containerised (Docker) environments
- Integrating Python applications with Azure services such as Azure Functions, Key Vault, and Blob Storage
- Working closely with DevOps and engineering teams to support CI/CD pipelines
- Debugging, tuning, and improving Python and Spark workloads in production
- Following best practices in secure Python development, cloud security, and data governance
What we're looking for:
- Strong, hands-on Python development experience (essential)
- Proven experience writing test-driven Python code in production environments
- Solid data engineering experience using PySpark
- Experience working with Delta Lake
- Hands-on experience with Docker and containerised workflows
- Good knowledge of Azure and integrating Python applications with cloud services
- A software-engineering mindset and comfort working in fast-paced, delivery-focused teams
Python Data Engineer employer: Brightbox GRP Ltd
Contact Detail:
Brightbox GRP Ltd Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Python Data Engineer
✨Tip Number 1
Network like a pro! Reach out to your connections in the data engineering field, especially those who work with Python and Azure. A friendly chat can lead to insider info about job openings or even referrals.
✨Tip Number 2
Show off your skills! Create a GitHub repository showcasing your Python projects, especially those involving data pipelines and PySpark. This gives potential employers a taste of your coding style and problem-solving abilities.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python fundamentals and testing practices. Be ready to discuss your experience with Delta Lake and Docker, as well as how you approach building scalable data solutions.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Plus, it’s a great way to ensure your application gets the attention it deserves.
We think you need these skills to ace Python Data Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your Python development experience and any relevant projects you've worked on. We want to see how your skills align with the role, so don’t be shy about showcasing your best work!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about data engineering and how your experience with Python and PySpark makes you a perfect fit for our team. Keep it engaging and personal!
Showcase Your Testing Skills: Since we value clean, maintainable code, make sure to mention your experience with unit tests and BDD tests. We love candidates who take testing seriously, so share examples of how you've implemented these in your past projects.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the easiest way for us to keep track of your application and ensures you’re considered for the role. Plus, it shows you’re keen to join our team!
How to prepare for a job interview at Brightbox GRP Ltd
✨Know Your Python Inside Out
Make sure you brush up on your Python fundamentals before the interview. Be ready to discuss your experience with writing clean, maintainable code and how you've implemented test-driven development in your previous projects.
✨Showcase Your Data Engineering Skills
Prepare to talk about your experience with data pipelines and PySpark. Have specific examples ready that demonstrate how you've designed and built scalable data flows, and be ready to explain the architecture behind them.
✨Familiarise Yourself with Azure Services
Since this role involves integrating Python applications with Azure services, make sure you understand how Azure Functions, Key Vault, and Blob Storage work. Being able to discuss how you've used these services in past projects will give you an edge.
✨Emphasise Collaboration and CI/CD Experience
This position requires working closely with DevOps and engineering teams. Be prepared to share your experiences with CI/CD pipelines and how you've collaborated with others to improve workflows and debugging processes.
