At a Glance
- Tasks: Define and evolve enterprise data models to support analytics and AI/ML use cases.
- Company: Sanderson, a leading data-driven organisation in Bristol.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Join a dynamic team and drive innovation in a complex data landscape.
- Why this job: Shape the future of data modelling and make a significant impact on business intelligence.
- Qualifications: Experience in data modelling and a strong understanding of data governance.
The predicted salary is between 70000 - 90000 £ per year.
Sanderson in Bristol is seeking a Principal Data Modeller to define, own and evolve the enterprise data model within a complex, data-driven organisation.
This senior individual contributor role acts as the design authority for data modelling, ensuring data assets support analytics, reporting, regulatory needs and AI/ML use cases.
You will work across multiple domains, align key business concepts, and enable scalable, reusable data products while guiding data governance and quality frameworks.
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Principal Data Modeller — Enterprise Data (Snowflake/AWS) employer: Sanderson
At Sanderson, we pride ourselves on being an excellent employer, offering a dynamic work culture that fosters collaboration and innovation in the heart of Belfast. Our commitment to employee growth is evident through tailored development programmes and opportunities for advancement, ensuring that our team members thrive in their careers while enjoying competitive rewards and a strong focus on health and safety compliance. Join us to take ownership of impactful projects and be part of a supportive environment that values your contributions.
StudySmarter Expert Advice🤫
We think this is how you could land Principal Data Modeller — Enterprise Data (Snowflake/AWS)
✨Get Involved in Data Science Meetups
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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 Sanderson.
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We think you need these skills to ace Principal Data Modeller — Enterprise Data (Snowflake/AWS)
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 Sanderson, 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 Sanderson. 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 Sanderson
✨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 Sanderson!
✨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.
