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- Tasks: Join our data team as an Analytics Engineer, shaping data assets and delivering insights.
- Company: Be part of a dynamic 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 industry meetups or webinars to connect with potential colleagues and learn more about the company culture.
✨Tip Number 3
Prepare to discuss your previous projects in detail, particularly those that involved data modelling and transformation. Be ready to explain your thought process and the impact of your work on business outcomes.
✨Tip Number 4
Showcase your communication skills by practising how you would explain complex data concepts to non-technical stakeholders. This will highlight your ability to collaborate effectively within teams and across departments.
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 the role, so make it clear how you excel in this area.
Highlight Project Ownership: Discuss any previous experiences where you took ownership of projects. Detail how you shaped data assets and collaborated with teams to deliver impactful results, as this aligns with the responsibilities of the role.
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. Bring examples of projects where you've used these technologies, especially focusing on data modelling and transformation.
✨Demonstrate Your Problem-Solving Abilities
Analytics engineering often involves tackling complex problems. Be ready to share specific instances where you've successfully solved challenges in data engineering or BI roles, highlighting your thought process.
✨Communicate Clearly
Strong communication skills are essential for this role. Practice explaining technical concepts in a way that non-technical stakeholders can understand, as collaboration with various teams will be key.
✨Prepare Questions About the Role
Show your interest in the position by preparing thoughtful questions about the team dynamics, project ownership, and the technologies they use. This demonstrates your enthusiasm and helps you assess if it's the right fit for you.
