At a Glance
- Tasks: Design and build scalable analytical data models for business intelligence and reporting.
- Company: Join a dynamic team at a leading data-driven organisation in London.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on innovation and continuous improvement.
- Why this job: Make an impact by transforming raw data into valuable insights for various teams.
- Qualifications: Advanced SQL skills and experience with analytical data models required.
The predicted salary is between 55000 - 65000 £ per year.
We are seeking an Analytics Engineer to design and build scalable analytical data models that support business intelligence, reporting and commercial analytics. The role sits within a multidisciplinary data team responsible for delivering trusted analytical data products used across Digital, Commercial, Service and Marketing teams. The ideal candidate will combine strong analytical thinking with advanced SQL engineering capability, and will have experience designing analytics-ready datasets used by BI tools or semantic layers.
What you’ll be doing:
- Drives the design, coding, testing and deployment of data processes for ingestion, transformation and curation of data, ensuring compliance with data security and privacy standards.
- Builds strong working relationships with product teams and stakeholders to translate business needs into clear analytical requirements and solution designs.
- Ensures effective tracking, integration and optimisation of data within analytics environments, maintaining data quality and accessibility.
- Monitors and interprets key reporting metrics (e.g., revenue, consumption, operational KPIs) to enable accurate performance tracking and insight generation.
- Leads the delivery of Agile routines and ways of working, ensuring consistent, high quality and iterative delivery of analytical outputs.
- Identifies and implements enhancements to data analytics processes, driving improvements to efficiency, reliability and scalability.
- Analyses business needs and evaluates solution options, facilitating stakeholder alignment and contributing to the development of data driven strategies.
- Undertakes quality assurance and testing of analytical routines, data models and frameworks to ensure accuracy, robustness and suitability for business use.
- Support the evolution of the organisation’s analytics data layer and self-service reporting capability.
- Develop robust SQL transformations to convert raw source data into trusted analytical assets.
- Design and implement scalable analytical data models in SQL used by BI tools and analytics platforms.
Essential Skills / Experience:
- Advanced SQL skills with experience engineering complex analytical transformations.
- Proven experience building analytical data models used by BI tools or reporting platforms with experience designing analytics-ready datasets rather than ingestion pipelines.
- Strong experience with cloud data warehouse platforms (preferably Google BigQuery / GCP).
Desirable Skills / Experience:
- Experience in working with digital data sources and data types. (Experience in working with Adobe Analytics advantageous).
- Experience working in commercial or marketing analytics environments.
- Experience designing consistent business metrics used across reporting and analytics.
- Experienced in building analytics-ready datasets used by BI tools and reporting platforms.
- Exposure to AI-enabled analytics tools or modern data workflows.
- Collaborative and comfortable working within cross-functional data teams.
Candidate Profile:
- Strong analytical mindset combined with engineering discipline.
- Comfortable working with complex business data and translating it into analytical structures.
- Experienced in building analytics-ready datasets used by BI tools and reporting platforms.
- Collaborative and comfortable working within cross-functional data teams.
- Commercially savvy, with the ability to translate complex information to senior stakeholders.
- Passion for data analysis and problem solving with a proactive and analytical approach.
Digital Analytics Engineer employer: 慨正橡扯
At our London office, we pride ourselves on fostering a dynamic and inclusive work culture that encourages innovation and collaboration. As a Digital Analytics Engineer, you will have access to cutting-edge technology and the opportunity to work alongside a talented multidisciplinary team, driving your professional growth through continuous learning and development. We offer competitive benefits and a supportive environment that values your contributions, making it an excellent place for those seeking meaningful and rewarding employment.
StudySmarter Expert Advice🤫
We think this is how you could land Digital Analytics Engineer
✨Network Like a Pro
Get out there and connect with people in the industry! Attend meetups, webinars, or even just grab a coffee with someone who works in digital analytics. Building relationships can open doors that a CV just can't.
✨Show Off Your Skills
Don’t just talk about your SQL skills—show them! Create a portfolio of projects or case studies that highlight your analytical prowess. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Ace the Interview
Prepare for common interview questions but also be ready to discuss specific projects you've worked on. Use the STAR method (Situation, Task, Action, Result) to structure your answers and demonstrate your problem-solving skills.
✨Apply Through Our Website
When you find a role that excites you, apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are genuinely interested in joining our team.
We think you need these skills to ace Digital Analytics Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV speaks directly to the role of Digital Analytics Engineer. Highlight your advanced SQL skills and any experience with BI tools or cloud data warehouses like Google BigQuery. We want to see how your background aligns with what we’re looking for!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re passionate about data analytics and how your experience can help us at StudySmarter. Don’t forget to mention specific projects or achievements that showcase your analytical mindset.
Showcase Your Analytical Projects:If you've worked on any relevant projects, make sure to include them in your application. Whether it's building analytical data models or optimising data processes, we love seeing real examples of your work that demonstrate your skills and problem-solving abilities.
Apply Through Our Website:We encourage you to apply through our website for the best chance of getting noticed. It’s super easy, and you’ll be able to submit all your materials in one go. Plus, it helps us keep track of your application better!
How to prepare for a job interview at 慨正橡扯
✨Know Your SQL Inside Out
As a Digital Analytics Engineer, your SQL skills are crucial. Brush up on advanced SQL techniques and be ready to discuss your experience with complex analytical transformations. Prepare to showcase specific examples of how you've built analytical data models that support BI tools.
✨Understand the Business Needs
Make sure you can articulate how you've translated business requirements into analytical solutions in the past. Think about times when you collaborated with product teams or stakeholders to deliver data-driven strategies. This will show your ability to align analytics with business goals.
✨Familiarise Yourself with Cloud Platforms
Since experience with cloud data warehouse platforms like Google BigQuery is essential, do some research on its features and capabilities. Be prepared to discuss how you've used such platforms in previous roles, especially in relation to data ingestion and transformation.
✨Showcase Your Problem-Solving Skills
Highlight your passion for data analysis and problem-solving during the interview. Prepare examples of challenges you've faced in analytics and how you approached them. This will demonstrate your proactive mindset and analytical approach, which are key for this role.
