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- Tasks: Enhance data foundations and build scalable models for impactful product decisions.
- Company: Leading AI video platform based in London with a focus on innovation.
- Benefits: Competitive salary, stock options, and a hybrid working environment.
- Why this job: Join a dynamic team and shape the future of data-driven decision-making.
- Qualifications: 4+ years in analytics engineering, strong dbt knowledge, and SQL proficiency.
- Other info: Collaborative culture with opportunities for professional growth.
The predicted salary is between 36000 - 60000 £ per year.
A leading AI video platform in London seeks an Analytics Engineer to enhance data foundations for product decision-making. The role requires collaboration with various teams to build scalable data models, ensuring data quality and trust.
Ideal candidates have over 4 years of experience in analytics engineering, strong dbt knowledge, and proficiency in SQL.
This position offers a competitive salary, stock options, and a hybrid working environment.
Analytics Engineer: Build Scalable Data Foundations Remote employer: Synthesia
Contact Detail:
Synthesia Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Analytics Engineer: Build Scalable Data Foundations Remote
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those already working at companies you're eyeing. A friendly chat can open doors and give you insider info that could help you stand out.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your best work in analytics engineering. Include projects where you've built scalable data models or improved data quality. This will give potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on your SQL and dbt knowledge. Be ready to discuss how you've tackled challenges in past roles and how you can contribute to building robust data foundations in their team.
✨Tip Number 4
Don't forget to apply through our website! We make it easy for you to showcase your skills and experience directly to us. Plus, it shows you're genuinely interested in joining our team!
We think you need these skills to ace Analytics Engineer: Build Scalable Data Foundations Remote
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in analytics engineering and showcases your strong dbt knowledge and SQL proficiency. We want to see how your skills align with the role, so don’t be shy about tailoring it to fit!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re excited about the role and how you can contribute to building scalable data foundations. Let us know what makes you the perfect fit for our team.
Showcase Your Projects: If you've worked on any relevant projects, make sure to mention them! We love seeing real-world examples of your work, especially those that demonstrate your ability to enhance data quality and trust.
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 don’t miss out on any important updates from our team!
How to prepare for a job interview at Synthesia
✨Know Your Data Tools
Make sure you brush up on your dbt and SQL skills before the interview. Be ready to discuss how you've used these tools in past projects, as this will show your practical experience and understanding of scalable data models.
✨Showcase Collaboration Skills
Since the role involves working with various teams, prepare examples of how you've successfully collaborated in the past. Highlight any cross-functional projects where you enhanced data quality or trust, as this will demonstrate your ability to work well with others.
✨Prepare for Technical Questions
Expect some technical questions related to analytics engineering. Review common scenarios you might face in the role and think through your problem-solving approach. This will help you articulate your thought process clearly during the interview.
✨Ask Insightful Questions
At the end of the interview, don’t forget to ask questions that show your interest in the company and the role. Inquire about their current data challenges or how they envision the analytics engineer contributing to product decision-making. This shows you're genuinely interested and engaged.
