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For Companies At a Glance
- Tasks: Design and maintain scalable analytics models to deliver trusted insights.
- Company: Join a global, design-led market leader in analytics.
- Benefits: Inclusive workplace, skill development, and collaborative culture.
- Why this job: Shape the future of analytics and influence data-driven decisions.
- Qualifications: Strong analytical skills, advanced SQL, and experience with modern ELT tools.
- Other info: Empowering environment with opportunities for growth and innovation.
The predicted salary is between 30000 - 40000 £ per year.
We’re looking for an experienced Analytics Engineer to help shape our data foundations and deliver high quality, trusted insights across the business. You’ll design and maintain scalable analytics models, ensure data quality, and work closely with teams across Finance, Commercial, Operations, and IT to turn complex requirements into intuitive, reliable datasets. This role sits at the heart of our analytics function, balancing immediate reporting needs with long‑term data architecture, and ensuring our organisation can make confident, data driven decisions.
Key Responsibilities
- Design, build, and maintain analytics models that convert raw data into trusted, business-ready datasets.
- Own the full modelling lifecycle (staging → core → marts).
- Define and maintain consistent metrics, dimensions, and business logic.
- Implement testing, data quality checks, and SLAs to ensure reliability.
- Translate business requirements into scalable, well‑structured data solutions.
- Deliver self‑service datasets and support reporting/dashboards where needed.
- Continuously improve analytics engineering processes and standards.
- Provide robust data foundations to support strategic initiatives, including cost, pricing, and operational analytics.
What We Are Looking For
- We’re seeking someone with strong analytical and technical capability, who enjoys solving complex data problems and can confidently partner with stakeholders across the business.
- You’ll bring the ability to design robust data models, communicate clearly, and ensure outputs are accurate, consistent, and actionable.
- A degree in Computer Science, Engineering, Maths, Economics, Data Science is desirable.
- Advanced SQL skills and experience with analytical/dimensional modelling.
- Practical experience with modern ELT tools (Dataform/dbt) and Git workflows.
- Knowledge of cloud data warehouses, ideally BigQuery.
- Familiarity with orchestration tools such as Airflow.
- Experience designing BI‑friendly datasets, particularly for Power BI.
- Strong communication skills, able to translate business needs into data models.
- Experience with enterprise systems such as SAP BW/HANA.
- A track record of building reusable datasets or maintaining a metrics/semantic layer.
- Basic Python for automation or analytics engineering tooling.
- Experience collaborating in cross‑functional analytics or data product teams.
Why Join Us
- Help shape the future of analytics at a global, design‑led market leader.
- Work collaboratively across Finance, Commercial, Operations, IT, and more.
- Have real influence on how data is defined, trusted, and used across the organisation.
- Join a supportive, innovative culture known for empowering teams and encouraging growth.
- Develop your skills with modern cloud, modelling, and automation technologies.
- We understand there’s no one size fits all approach. We’re proud to offer an inclusive workplace where every colleague feels valued, supported, and empowered to be their true self.
- If you require any reasonable adjustments throughout the recruitment process, please let us know and we’ll be happy to accommodate.
- Everyone who applies will receive a response.
Junior Analytics Engineer employer: Hillarys Blinds Limited
Contact Detail:
Hillarys Blinds Limited Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Junior Analytics Engineer
✨Tip Number 1
Network like a pro! Reach out to folks 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 put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your analytics models and projects. This is your chance to demonstrate your technical capabilities and problem-solving skills, making you stand out from the crowd.
✨Tip Number 3
Prepare for interviews by practising common questions related to analytics engineering. Be ready to discuss your experience with SQL, ELT tools, and how you've tackled complex data problems in the past. Confidence is key!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, it shows you’re genuinely interested in joining our team and shaping the future of analytics together.
We think you need these skills to ace Junior Analytics Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the Junior Analytics Engineer role. Highlight your analytical capabilities, SQL skills, and any relevant projects you've worked on. We want to see how you can contribute to our data foundations!
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 your background aligns with our needs. Be sure to mention your experience with ELT tools and cloud data warehouses, as these are key for us.
Showcase Your Projects: If you've worked on any relevant projects, whether in school or professionally, make sure to include them. We love seeing practical examples of your work, especially if they involve building datasets or using BI tools like Power BI.
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 gives you a chance to explore more about our culture and values!
How to prepare for a job interview at Hillarys Blinds Limited
✨Know Your Data Models
Before the interview, brush up on your understanding of analytics models and how they convert raw data into business-ready datasets. Be prepared to discuss your experience with the full modelling lifecycle and how you've implemented testing and data quality checks in past projects.
✨Showcase Your Technical Skills
Make sure you can confidently talk about your advanced SQL skills and any experience you have with ELT tools like Dataform or dbt. If you've worked with cloud data warehouses like BigQuery, be ready to share specific examples of how you've used these technologies to solve complex data problems.
✨Communicate Clearly
Since this role involves collaborating with various teams, practice explaining technical concepts in a way that non-technical stakeholders can understand. Think of examples where you've successfully translated business requirements into scalable data solutions and how that impacted decision-making.
✨Prepare for Scenario Questions
Expect questions that ask you to solve hypothetical data challenges or improve existing processes. Prepare by thinking through past experiences where you had to design BI-friendly datasets or automate tasks using Python, and be ready to discuss your thought process and outcomes.