At a Glance
- Tasks: Design and build a scalable data warehouse while optimising ETL/ELT pipelines.
- Company: Join Ardanis, a forward-thinking IT services company in the hospitality sector.
- Benefits: Enjoy hybrid or remote work options after initial on-site training.
- Other info: Great opportunity for career growth in a dynamic environment.
- Why this job: Make a real impact by enhancing data insights and reporting with Power BI.
- Qualifications: Experience as a Data Engineer with strong SQL and Power BI skills.
The predicted salary is between 45000 - 55000 £ per year.
Overview
Ardanis is currently looking for a Data Engineer to support a client in the hospitality sector in the UK.
The role involves collaborating with a small, non-technical internal team to build and refactor a data warehouse, streamline reporting, and improve insights through Power BI.
The engagement will begin with on-site presence in the UK for the first few weeks to work directly with the client team.
After this initial phase, you can work both hybrid or remote.
Responsibilities
- Design, build, and refactor a scalable data warehouse solution.
- Develop and optimize ETL/ELT pipelines for data integration and reliability.
- Support the enhancement of Power BI dashboards and reports.
- Train and upskill a small internal team to ensure knowledge transfer.
- Introduce best practices in data governance, documentation, and reporting.
Requirements
- Proven experience as a Data Engineer or in a similar role.
- Strong knowledge of data warehouse design, SQL, and ETL/ELT processes.
- Hands-on experience with Power BI (data modeling, DAX, report optimization).
- Ability to collaborate effectively with non-technical stakeholders.
- Excellent communication and problem-solving skills.
- Availability to work on-site in the UK for the first weeks of the project.
- Nice to Have
- Previous experience in the hospitality industry or with transactional/operational data.
- Familiarity with cloud platforms (Azure, AWS, or GCP).
- Knowledge of data governance and compliance standards.
- Additional Details
- Seniority level: Mid-Senior level
- Employment type: Full-time
- Job function: Other
- Industries: IT Services and IT Consulting
- #J-18808-Ljbffr
Data Engineer employer: Ardanis
Ardanis is an exceptional employer, offering a dynamic work environment where innovation meets collaboration. With a focus on employee growth, you will have the opportunity to enhance your skills while working closely with a supportive team in the hospitality sector. The hybrid and remote work options after the initial on-site phase provide flexibility, making it an attractive place for those seeking meaningful and rewarding employment.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer
✨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 Ardanis!
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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 Ardanis.
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When you find a suitable opening like Data Engineer at Ardanis, 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 Data Engineer
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 Ardanis, 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 Ardanis. 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 Ardanis
✨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 Ardanis!
✨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.
