At a Glance
- Tasks: Design and build scalable data pipelines using Azure services in a dynamic cloud environment.
- Company: Join a forward-thinking company in Warwick, UK, focused on data-driven solutions.
- Benefits: Competitive day rate, hands-on experience with cutting-edge technologies, and a collaborative team.
- Other info: Fast-paced environment with opportunities for professional growth and development.
- Why this job: Make an impact by optimising data solutions and enabling data-driven decisions.
- Qualifications: Experience with Azure Data Factory, Databricks, Python, and strong SQL skills required.
The predicted salary is between 50000 - 60000 £ per year.
This role is for an experienced Azure Data Engineer to support the design, development and optimisation of data solutions within a modern cloud-based environment. The successful candidate will contribute to building scalable and reliable data pipelines, enabling data-driven decision-making across the organisation. Working within a fast-paced delivery environment, the role offers exposure to cloud technologies and advanced data platforms, supporting the transformation and integration of large and complex datasets. The position plays a key role in ensuring data quality, accessibility and performance across business‐critical systems.
Key responsibilities
- Design, build and maintain scalable data pipelines using Azure data services
- Develop and manage data integration workflows using Azure Data Factory
- Perform data transformation and processing using tools such as Databricks and Python
- Troubleshoot and debug data pipelines to ensure reliability and performance
- Collaborate with stakeholders to understand data requirements and translate them into technical solutions
- Optimise data storage and processing using platforms such as Snowflake
- Ensure data quality, governance and security standards are maintained
- Support deployment and monitoring of data solutions in production environments
- Document data processes and maintain technical documentation
Key skills, knowledge and experience
- Strong experience with Azure data services, including Azure Data Factory
- Advanced expertise in Azure Data Factory development and optimisation
- Experience working with Snowflake for data warehousing solutions
- Hands‐on experience with Databricks for large-scale data processing
- Proficiency in Python for data engineering tasks
- Strong SQL knowledge and experience working with relational databases
- Experience in debugging and resolving data pipeline issues
- Understanding of data architecture and best practices in data engineering
- Good communication skills with the ability to work collaboratively
Desirable skills, knowledge and experience
- 6 to 8 years of relevant data engineering experience
- Exposure to additional cloud data platforms or modern data stack tools
- Experience working in agile delivery environments
Azure Data Engineer in Warwick employer: Stott & May
As an Azure Data Engineer at our Warwick office, you will join a dynamic team that values innovation and collaboration, providing you with the opportunity to work on cutting-edge cloud technologies. We offer a supportive work culture that prioritises employee growth through continuous learning and development, alongside competitive remuneration and benefits. Our commitment to data excellence ensures that you will play a pivotal role in transforming complex datasets into actionable insights, making your contributions both meaningful and rewarding.
StudySmarter Expert Advice🤫
We think this is how you could land Azure Data Engineer in Warwick
✨Tip Number 1
Network like a pro! Reach out to your connections in the data engineering field, especially those who work with Azure. A friendly chat can lead to insider info about job openings that aren't even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Azure Data Factory and Databricks. 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 common data engineering scenarios. Be ready to discuss how you've tackled challenges in building scalable data pipelines or optimising data storage. We want to see your problem-solving skills in action!
✨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 Azure Data Engineer in Warwick
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with Azure data services 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 expertise in Azure Data Factory and Snowflake!
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 you can contribute to our team. We love seeing candidates who can communicate their enthusiasm for cloud technologies and data-driven decision-making.
Showcase Your Projects:If you've worked on any cool data projects, make sure to mention them! Whether it's building data pipelines or optimising workflows, we want to hear about your hands-on experience. Include links to your GitHub or any relevant portfolios if you have them.
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 gives you a chance to explore more about what we do at StudySmarter!
How to prepare for a job interview at Stott & May
✨Know Your Azure Data Services
Make sure you brush up on your knowledge of Azure Data Factory and other Azure data services. Be ready to discuss your hands-on experience and any specific projects where you've designed or optimised data pipelines. This will show that you’re not just familiar with the tools, but that you can effectively use them in real-world scenarios.
✨Showcase Your Problem-Solving Skills
Prepare to talk about times when you've troubleshot and debugged data pipelines. Think of specific examples where you identified issues and how you resolved them. This will demonstrate your ability to maintain reliability and performance in data solutions, which is crucial for the role.
✨Communicate Clearly with Stakeholders
Since collaboration is key, practice explaining technical concepts in a way that non-technical stakeholders can understand. You might be asked how you would gather data requirements or translate them into technical solutions, so having a clear communication strategy will set you apart.
✨Familiarise Yourself with Data Governance
Understand the importance of data quality, governance, and security standards. Be prepared to discuss how you’ve ensured these standards in past roles, especially in relation to large datasets. This shows that you take data integrity seriously, which is vital for any data engineering position.
