At a Glance
- Tasks: Design and build data solutions using Azure and Microsoft Fabric for exciting projects.
- Company: Join a leading tech firm focused on innovative data solutions.
- Benefits: Competitive salary, remote work options, and opportunities for professional growth.
- Other info: Dynamic team environment with a focus on collaboration and continuous learning.
- Why this job: Be part of transformative projects that shape the future of data engineering.
- Qualifications: Experience with Azure Data Factory, SQL, and modern data architectures required.
The predicted salary is between 60000 - 65000 £ per year.
Our client is seeking a Data Engineer to join their UK team and help to deliver an exciting programme of work that began this year. With a D365 programme and the delivery of a Laboratory Information Management System application due to go ahead in the coming months, now is a great time to be joining their team. The Data Engineer will contribute to the design and build of required infrastructure to support optimal extraction, transformation, and load of data from various sources.
Responsible for (but not limited to) the following:
- Design and deliver end-to-end data solutions across Azure and Microsoft Fabric platforms.
- Develop and optimise enterprise-grade Power BI semantic models and reporting solutions.
- Build and maintain scalable, high-performance data pipelines using Azure Data Factory and Fabric.
- Engineer lakehouse architectures using medallion layers (Bronze, Silver, Gold).
- Design and implement star schemas and analytical data models aligned to business needs.
- Develop and optimise data transformations using PySpark/Spark.
- Integrate data from on-premises and cloud systems into centralised platforms.
- Create reusable pipelines, datasets, and data components to improve delivery efficiency.
- Ensure data quality, performance, governance, and reliability across all data assets.
- Implement DataOps practices including CI/CD, monitoring, version control, and production support.
Qualifications:
- Bachelor’s degree in computer science, Engineering, or equivalent experience.
- Strong experience with Azure Data Factory and modern data integration patterns.
- Advanced Power BI capability.
- Strong proficiency in SQL and data modelling for analytics-ready solutions.
- Experience with Azure cloud data platforms and modern data architectures.
- Knowledge or experience of Microsoft Fabric, including lakehouse/warehouse concepts and Power BI integration.
- Experience with PySpark/Spark-based data processing.
- Understanding of DataOps principles, including CI/CD, automated testing, monitoring, and data lifecycle management.
- Aware of enterprise data needs, including AI/ML enablement, governance, security, reusable data assets, plus strong problem-solving, collaboration, and continuous learning mindset.
Location: Cambridge/Hybrid
Candidates must be eligible to work in this country.
Azure Data Engineer in Cambridge employer: Catch Resource Management
Catch Resource Management is an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration in the heart of Cambridge. With a strong focus on employee growth, we provide opportunities for continuous learning and development in cutting-edge technologies like Azure and Power BI, ensuring our team members are at the forefront of the data engineering field. Join us to be part of an exciting journey as we deliver impactful solutions while enjoying the flexibility of a hybrid working environment.
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We think this is how you could land Azure Data Engineer in Cambridge
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Catch Resource Management.
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We think you need these skills to ace Azure Data Engineer in Cambridge
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Catch Resource Management, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Catch Resource Management. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Catch Resource Management
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Catch Resource Management!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
