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- Tasks: Join a dynamic team to design and optimise data platforms using Azure and Databricks.
- Company: A leading organisation driving digital transformation with a focus on innovative data solutions.
- Benefits: Enjoy flexible hybrid working, exposure to modern technologies, and opportunities in analytics and AI.
- Why this job: Be part of a collaborative culture that values innovation and data-driven decision-making.
- Qualifications: Experience with Databricks, Azure Data Lake, Python, and Agile methodologies is essential.
- Other info: Candidates must have valid UK work authorisation; sponsorship is not available.
The predicted salary is between 39000 - 65000 £ per year.
A well-established, forward-thinking organisation at the forefront of digital transformation is expanding its data capability. With a strong focus on delivering high-quality data solutions and embracing cutting-edge technology, this business supports strategic analytics and AI initiatives across the board. They offer a collaborative environment, modern hybrid working options, and are committed to innovation through cloud-based infrastructure and agile methodologies. This is an excellent opportunity for a skilled Database Engineer to join a growing data team.
The role will focus on building and optimising modern data platforms, particularly a lakehouse architecture on Microsoft Azure and Databricks. You'll be part of an agile team working to enable data-driven decision-making through scalable engineering practices.
Key Responsibilities of the Database Engineer:- Design and build scalable data pipelines and ETL processes using Databricks and Delta Live Tables
- Develop robust solutions on Azure, enhancing the lakehouse architecture with Spark technologies
- Implement automated CI/CD pipelines for streamlined testing and deployment
- Collaborate with cross-functional teams to deliver data solutions that support analytics and AI initiatives
- Proven experience with Databricks, Azure Data Lake, and Delta Live Tables
- Strong programming in Python and Spark (PySpark or Scala)
- Solid knowledge of data modelling, warehousing, and integration concepts
- Comfortable working in Agile teams, with CI/CD and Azure DevOps experience
- Flexible hybrid working arrangements
- Exposure to a wide range of modern data technologies
- Opportunity to contribute to cutting-edge analytics and AI projects
Note on Sponsorship: We regret to inform you that at this time, we are unable to offer sponsorship for work authorisation for this role. Therefore, candidates must possess valid authorisation to work in the UK without requiring visa sponsorship now or in the future.
Database Engineer employer: CA Tech Talent
Contact Detail:
CA Tech Talent Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Database Engineer
✨Tip Number 1
Familiarise yourself with the latest trends in data engineering, particularly around lakehouse architecture and Azure technologies. This will not only help you understand the role better but also allow you to engage in meaningful conversations during interviews.
✨Tip Number 2
Showcase your experience with Databricks and Delta Live Tables by working on personal projects or contributing to open-source initiatives. This hands-on experience can be a great talking point and demonstrate your practical skills to potential employers.
✨Tip Number 3
Network with professionals in the data engineering field through platforms like LinkedIn or local meetups. Engaging with others in the industry can provide insights into the company culture and may even lead to referrals.
✨Tip Number 4
Prepare for technical interviews by practising coding challenges related to Python and Spark. Websites like LeetCode or HackerRank can be useful for honing your skills and boosting your confidence before the interview.
We think you need these skills to ace Database Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Databricks, Azure Data Lake, and Delta Live Tables. Emphasise your programming skills in Python and Spark, as well as any relevant projects that showcase your ability to build scalable data pipelines.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Mention specific projects or technologies you have worked with that align with the job description, particularly focusing on your experience with cloud-based infrastructure and agile methodologies.
Showcase Relevant Projects: If you have worked on any projects involving data modelling, warehousing, or integration concepts, be sure to include these in your application. Highlight your contributions and the impact of your work on data-driven decision-making.
Proofread Your Application: Before submitting your application, take the time to proofread your CV and cover letter. Check for any spelling or grammatical errors, and ensure that all information is clear and concise. A polished application reflects your attention to detail.
How to prepare for a job interview at CA Tech Talent
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Databricks, Azure Data Lake, and Delta Live Tables in detail. Bring examples of projects where you've successfully implemented these technologies, as this will demonstrate your hands-on expertise.
✨Understand the Agile Methodology
Since the role involves working in Agile teams, make sure you can articulate your understanding of Agile principles. Be ready to share how you've contributed to Agile projects in the past, particularly in relation to CI/CD processes.
✨Prepare for Problem-Solving Questions
Expect technical questions that assess your problem-solving abilities, especially around data pipeline design and optimisation. Practise explaining your thought process clearly, as this will show your analytical skills and ability to communicate complex ideas.
✨Demonstrate Collaboration Skills
The role requires collaboration with cross-functional teams, so be ready to discuss how you've worked effectively with others in previous roles. Highlight any experiences where you contributed to team success or supported analytics and AI initiatives.
