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- Tasks: Join our data team as an Analytics Engineer, shaping data assets and delivering insights.
- Company: Be part of a forward-thinking company in Leeds, focused on cutting-edge data technologies.
- Benefits: Enjoy flexible working with 3 days in the office and opportunities for professional growth.
- Why this job: Work with innovative tools like Snowflake and Azure, making a real impact on data-driven decisions.
- Qualifications: Experience in analytics engineering, proficiency in SQL, and hands-on with dbt required.
- Other info: UK residents only; no sponsorship available.
My client is looking for an experienced Analytics Engineer to join their expanding data team. They are looking for someone who can work in their Leeds office 3 days per week. You will work with cutting-edge technologies Snowflake, DBT, Azure and Power BI and have the chance to have ownership over projects and shape data assets.
As an Analytics Engineer, you'll collaborate with teams to design and deliver scalable data models that unlock insights across customer, product, and operational domains.
Requirements:
- Proven experience in analytics engineering or BI/data roles with a focus on data modelling and transformation.
- Proficiency in SQL and cloud data platforms like Snowflake or Azure Synapse Analytics.
- Hands-on experience with dbt for developing, testing, and documenting transformations.
- Strong communication skills.
- Ability to build scalable, high-quality systems.
Please Note: This role is for UK residents only. This role does not offer Sponsorship. You must have the right to work in the UK with no restrictions. Some of our roles may be subject to successful background checks including a DBS and Credit Check.
Analytics Engineer employer: CV-Library
Contact Detail:
CV-Library Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Analytics Engineer
✨Tip Number 1
Familiarise yourself with the specific technologies mentioned in the job description, such as Snowflake, DBT, and Azure. Consider taking online courses or tutorials to enhance your skills and demonstrate your commitment to mastering these tools.
✨Tip Number 2
Network with professionals in the analytics engineering field, especially those who work with the technologies listed. Attend meetups or webinars to connect with potential colleagues and learn about industry trends that could give you an edge.
✨Tip Number 3
Prepare to discuss your previous projects in detail, particularly those involving data modelling and transformation. Be ready to explain your thought process and the impact of your work on business outcomes, as this will showcase your analytical skills.
✨Tip Number 4
Practice your communication skills, as strong communication is essential for this role. Consider mock interviews or discussions with peers to refine how you present complex data concepts in a clear and engaging manner.
We think you need these skills to ace Analytics Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in analytics engineering and BI/data roles. Emphasise your proficiency in SQL, cloud data platforms like Snowflake or Azure, and your hands-on experience with dbt.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for data modelling and transformation. Mention specific projects where you've successfully built scalable systems and how you can contribute to the company's data team.
Showcase Communication Skills: In your application, provide examples of how you've effectively communicated complex data insights to non-technical stakeholders. This is crucial for collaboration within teams.
Highlight Ownership Experience: Discuss any previous experiences where you took ownership of projects. Detail how you shaped data assets and the impact it had on the organisation, as this aligns with the role's responsibilities.
How to prepare for a job interview at CV-Library
✨Showcase Your Technical Skills
Be prepared to discuss your experience with SQL, Snowflake, and Azure Synapse Analytics. Bring examples of past projects where you used these technologies, and be ready to explain your approach to data modelling and transformation.
✨Demonstrate Your Problem-Solving Abilities
Analytics engineering often involves tackling complex problems. Prepare to share specific instances where you've successfully solved challenges in data analysis or modelling, highlighting your thought process and the impact of your solutions.
✨Communicate Clearly
Strong communication skills are essential for this role. Practice explaining technical concepts in a way that non-technical stakeholders can understand. This will show your ability to collaborate effectively with different teams.
✨Prepare Questions About the Role
Show your interest in the position by preparing thoughtful questions about the company's data strategy, team dynamics, and the technologies they use. This not only demonstrates your enthusiasm but also helps you assess if the role is the right fit for you.
