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- Tasks: Design and maintain scalable data models for actionable insights across teams.
- Company: Join a forward-thinking tech company revolutionising data analytics.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Dynamic team environment with a focus on innovation and best practices.
- Why this job: Be at the forefront of data evolution and drive impactful decision-making.
- Qualifications: Experience in data modelling and strong collaboration skills required.
The predicted salary is between 60000 - 80000 £ per year.
We’re looking for an experienced Analytics Engineer to help build the next generation of Contentful’s analytics foundation, powering Insight 360, our unified Snowflake-based data platform.
In this role, you’ll design and maintain robust, scalable data models that make our business data accessible and actionable across all teams. You’ll collaborate with engineers, analysts, and business stakeholders to deliver high-quality, trusted datasets that enable data-driven decision-making across the company. Your work will sit at the heart of Contentful’s data evolution, helping us move to a modern, governed, and insight-led architecture.
Key Responsibilities
- Data Modeling & Transformation
- Design, build, and maintain efficient, scalable analytics models in dbt and Snowflake.
- Transform raw data from diverse domains (product, finance, sales, marketing, operations) into analytics-ready structures.
- Apply best practices in modularity, documentation, and testing to ensure long-term reliability.
- Pipeline Ownership
- Take ownership of analytics engineering projects end-to-end: from scoping requirements through implementation and monitoring.
- Develop reusable, maintainable data transformations that enable self-serve analytics in Tableau and other BI tools.
- Enablement & Collaboration
- Partner with analysts, data scientists, and business teams to define and deliver trusted data assets.
- Collaborate with data platform engineers to optimize performance, governance, and cost efficiency in Snowflake.
- Contribute to the shared data catalog and drive adoption of best practices across analytics and engineering teams.
What You’ll Need
Analytical Engineer f/m/d employer: Contentful
Contact Detail:
Contentful Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Analytical Engineer f/m/d
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data models and transformations. Use platforms like GitHub to share your projects and demonstrate your expertise in dbt and Snowflake. This will make you stand out when chatting with hiring managers.
✨Tip Number 3
Prepare for those interviews! Brush up on common analytics engineering questions and be ready to discuss your past projects. Practice explaining your thought process behind data modelling and how you’ve collaborated with teams to deliver results.
✨Tip Number 4
Don’t forget to apply through our website! We love seeing candidates who are genuinely interested in joining us. Tailor your application to highlight how your experience aligns with our mission of building a robust analytics foundation.
We think you need these skills to ace Analytical Engineer f/m/d
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the role of an Analytics Engineer. Highlight your experience with data modelling, transformation, and any relevant tools like dbt and Snowflake. We want to see how your skills align with our needs!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about analytics and how you can contribute to our data evolution. Be sure to mention any collaborative projects you've worked on that relate to the role.
Showcase Your Projects: If you've worked on any relevant projects, don’t hesitate to showcase them! Whether it's a personal project or something from a previous job, we love seeing practical examples of your work in data engineering and analytics.
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It helps us keep everything organised and ensures your application gets the attention it deserves. Plus, it’s super easy!
How to prepare for a job interview at Contentful
✨Know Your Data Models
Make sure you brush up on your knowledge of data modelling and transformation techniques. Be ready to discuss how you've designed and maintained scalable analytics models in the past, especially using tools like dbt and Snowflake.
✨Showcase Your Collaboration Skills
Since this role involves working closely with various teams, prepare examples of how you've successfully collaborated with engineers, analysts, and business stakeholders. Highlight any projects where teamwork led to impactful data-driven decisions.
✨Demonstrate Ownership
Be prepared to talk about a project where you took ownership from start to finish. Discuss how you scoped requirements, implemented solutions, and monitored outcomes. This will show your potential employer that you can handle end-to-end analytics engineering projects.
✨Emphasise Best Practices
Familiarise yourself with best practices in modularity, documentation, and testing. During the interview, mention how you apply these principles to ensure long-term reliability in your work. This will demonstrate your commitment to quality and governance in analytics.