At a Glance
- Tasks: Transform and model CRM data in Snowflake for impactful reporting and analytics.
- Company: Join a forward-thinking company driving major data transformation.
- Benefits: Flexible working, competitive pay, and opportunities for professional growth.
- Other info: Dynamic role with potential for significant career advancement.
- Why this job: Shape the future of data usage and influence key business decisions.
- Qualifications: Experience with Snowflake, SQL, and data modelling; teamwork skills essential.
The predicted salary is between 50000 - 70000 £ per year.
We're looking for an experienced Analytics Engineer to play a key role in a high-profile data transformation programme. You'll be responsible for transforming and modelling CRM data within Snowflake, building trusted data models and enabling high-quality reporting, analytics and insight across the organisation. Working closely with business stakeholders, analysts and engineering teams, you'll help define data requirements, improve data quality, and ensure data is accessible, reliable and fit for purpose.
Key skills:
- Snowflake
- SQL
- dbt
- Data Modelling
- Dynamics CRM (or similar CRM platforms)
- Git
- Understanding of Data Warehousing principles
Desirable:
- Python
- Experience supporting BI and analytics teams
- Exposure to modern data stack environments
This is an opportunity to influence how data is structured and consumed across the business, working at the heart of a major transformation programme and helping to establish best practice in analytics engineering. The role has been deemed Outside IR35, with onsite requirements driven by project needs rather than a fixed mandate.
Analytics Engineer in Coventry employer: Cadence Resourcing
Join a forward-thinking organisation that values innovation and collaboration, where as an Analytics Engineer, you will be at the forefront of a transformative data programme. Our supportive work culture fosters professional growth through continuous learning opportunities and encourages you to make a meaningful impact on data accessibility and quality. Located in a vibrant area, we offer a dynamic environment that champions creativity and teamwork, making it an excellent place for those seeking rewarding employment.
StudySmarter Expert Advice🤫
We think this is how you could land Analytics Engineer in Coventry
✨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 Cadence Resourcing.
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We think you need these skills to ace Analytics Engineer in Coventry
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!
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Craft a Tailored Cover Letter:For a full-time role at Cadence Resourcing, 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 Cadence Resourcing. 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 Cadence Resourcing
✨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 Cadence Resourcing!
✨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.
