At a Glance
- Tasks: Join our team to design and develop cutting-edge data pipelines and analytics solutions.
- Company: Dynamic global company focused on innovative data engineering and analytics.
- Benefits: Competitive salary, bonus scheme, hybrid work, healthcare, and career development.
- Other info: Join a diverse team with opportunities for growth and global events.
- Why this job: Make a real impact by transforming data into actionable insights for better decision-making.
- Qualifications: Experience in data engineering, SQL, and modern cloud-based analytics technologies.
The predicted salary is between 40000 - 50000 £ per year.
Data Engineer – Microsoft Fabric & Analytics Platform, based in our Cardiff office. We are seeking a Data Engineer to join our Business Intelligence team and help shape the next generation of our enterprise analytics platform. Our team is responsible for designing, developing, and maintaining the organisation's data platform, transforming data from multiple business systems into trusted, accessible, and actionable information. We work closely with stakeholders across the business to deliver scalable data solutions and intuitive Power BI reporting that support data-driven decision making.
We are currently evolving our architecture towards a modern Microsoft Fabric-based platform, leveraging Lakehouse and Delta Lake technologies to create a high-performance, scalable analytics environment capable of processing large volumes of data efficiently. This platform will form the foundation of future reporting, analytics, and data products across the organisation.
This role will play a key part in designing and building data ingestion pipelines, transforming and modelling data, and establishing best practices for our growing data platform.
- Design, develop, and maintain data pipelines using Microsoft Fabric and Azure technologies.
- Integrate data from multiple source systems, including Dynamics 365 CE, Dynamics 365 Finance & Operations, and other enterprise applications.
- Design and implement scalable data models to support reporting and analytics requirements.
- Develop robust data transformation, validation, and quality assurance processes.
- Work closely with business stakeholders, analysts, and report developers to understand data requirements and deliver effective solutions.
- Support the creation of high-quality, user-friendly Power BI datasets and reporting solutions.
- Maintain documentation covering data lineage, architecture, transformations, and business rules.
- Contribute to data governance, security, and platform best practices.
- Identify opportunities to improve platform performance, scalability, and maintainability.
Data Engineering
- Experience designing and developing data pipelines and ETL/ELT processes.
- Strong SQL skills with experience working on large datasets.
- Experience working with structured and semi-structured data sources such as SQL databases, JSON, CSV, XML, and APIs.
- Understanding of data modelling principles and analytical data structures.
- Experience troubleshooting data quality and performance issues.
Microsoft Data Platform
- Experience with Microsoft Fabric, Azure Synapse, Azure Data Factory, Databricks, or similar modern data platforms.
- Understanding of cloud-based data storage and processing concepts.
- Experience with Python, Spark, or PySpark.
- Understanding of how data structures support Power BI and analytical reporting.
- Experience preparing data for consumption by reporting and analytics teams.
- Experience with Power BI semantic models and performance optimisation.
- Experience with source control and DevOps practices.
We're looking for someone who enjoys solving data problems, building scalable solutions, and working with modern cloud-based analytics technologies. The ideal candidate will be passionate about creating a robust data platform that enables the business to make better decisions through trusted, accessible data.
Microsoft Data Engineer - Hybrid in Cardiff employer: Creditsafe
At Creditsafe, we pride ourselves on being an excellent employer, offering a dynamic work culture that fosters innovation and collaboration in our Cardiff office. As a Data Engineer, you'll benefit from a competitive salary, a hybrid working model, and ample opportunities for professional growth through e-learning and career development initiatives. Join us to be part of a diverse team dedicated to transforming data into actionable insights, while enjoying global company events and a supportive environment that values your contributions.
StudySmarter Expert Advice🤫
We think this is how you could land Microsoft Data Engineer - Hybrid in Cardiff
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Creditsafe!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Microsoft Data Engineer - Hybrid at Creditsafe.
✨Leverage Professional Networks
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 Creditsafe.
✨Apply Directly through Our Website
When you find a suitable opening like Microsoft Data Engineer - Hybrid at Creditsafe, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Microsoft Data Engineer - Hybrid in Cardiff
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 Creditsafe, 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 Creditsafe. 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 Creditsafe
✨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 Creditsafe!
✨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.
