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- Tasks: Build and maintain high-quality analytical data models for efficient querying.
- Company: Join Menlo Ventures, a supportive tech company in Bristol.
- Benefits: Enjoy 25 days annual leave, flexible working, and a great culture.
- Other info: Collaborate with cross-functional teams in a dynamic environment.
- Why this job: Make an impact by optimising data models and ensuring data quality.
- Qualifications: Proficient in SQL, data transformation, and experience with BI tools.
The predicted salary is between 50000 - 65000 £ per year.
Menlo Ventures is looking for a Senior Analytics Engineer to join our UK Engineering team in Bristol. This role focuses on building and maintaining high-quality analytical data models, working closely with cross-functional teams to ensure data quality, and creating optimized data models for efficient querying.
Key qualifications include:
- Proficiency in SQL
- Data transformation
- Experience with dbt
- BI tooling like PowerBI or Looker
Enjoy benefits such as 25 days annual leave, flexible working, and a supportive culture.
Senior Analytics Engineer - Data Modeling & BI (Hybrid) employer: Menlo Ventures
Contact Detail:
Menlo Ventures Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Analytics Engineer - Data Modeling & BI (Hybrid)
✨Tip Number 1
Network like a pro! Reach out to current employees at Menlo Ventures on LinkedIn. A friendly chat can give us insights into the company culture and maybe even a referral!
✨Tip Number 2
Show off your skills! Prepare a portfolio showcasing your best data models and BI projects. This will help us stand out during interviews and demonstrate our hands-on experience.
✨Tip Number 3
Practice makes perfect! Get comfortable with common interview questions for analytics roles. We can even do mock interviews with friends to boost our confidence.
✨Tip Number 4
Apply through our website! It’s the best way to ensure our application gets noticed. Plus, we can tailor our application to highlight how our skills match the job description perfectly.
We think you need these skills to ace Senior Analytics Engineer - Data Modeling & BI (Hybrid)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with SQL, data transformation, and any BI tools like PowerBI or Looker. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re excited about the Senior Analytics Engineer role and how your background makes you a perfect fit for our team at Menlo Ventures.
Showcase Your Analytical Skills: In your application, include examples of how you've built and maintained analytical data models in the past. We love seeing real-world applications of your skills, so share specific outcomes and impacts!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at Menlo Ventures
✨Know Your SQL Inside Out
Make sure you brush up on your SQL skills before the interview. Be prepared to discuss complex queries and how you've used SQL in past projects. Practising some real-world scenarios can help you demonstrate your proficiency effectively.
✨Showcase Your Data Modelling Experience
Be ready to talk about your experience with data modelling and transformation. Have specific examples from your previous roles where you built or optimised data models, especially using dbt. This will show that you understand the nuances of creating high-quality analytical models.
✨Familiarise Yourself with BI Tools
Since the role involves BI tooling like PowerBI or Looker, make sure you know the ins and outs of these platforms. If possible, prepare a mini-project or case study that highlights your ability to create insightful dashboards or reports using these tools.
✨Emphasise Collaboration Skills
This position requires working closely with cross-functional teams, so be prepared to discuss how you've collaborated with others in the past. Share examples of how you ensured data quality and communicated effectively with different stakeholders to achieve common goals.