At a Glance
- Tasks: Own the analytics layer and translate data needs into reliable models.
- Company: Join a forward-thinking company that values data-driven decisions.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Dynamic role with excellent career advancement potential.
- Why this job: Shape impactful data strategies and collaborate with diverse teams.
- Qualifications: 3+ years in Analytics Engineering and advanced SQL skills required.
The predicted salary is between 54450 - 66550 £ per year.
In this role you will own the analytics layer and serve as the main data contact across the business. You will translate data needs from Product, Marketing, Finance and Operations into reliable models and metrics, enabling clear stakeholder insight and senior-leader storytelling. You’ll shape data schemas, reporting and cost-efficient analytics on a scalable platform built on top of an existing ingestion layer. This is a hands-on role that combines modelling, reporting, and collaboration to drive data-driven decisions across the company.
Responsibilities
- Design and own data schemas and modelling layers
- Build core entity models (e.g., members, subscriptions, payments) and presentation models for reporting/BI
- Decide when to address requirements with a query vs a new model
- Own usability, performance, and cost of the reporting layer
- Collaborate with Omni and Snowflake to ensure scalable analytics infrastructure
- Identify opportunities to improve reporting performance and optimise costs
Key requirements
- 3+ years of Analytics Engineering or related data role
- Advanced SQL skills
- Experience with tested, version-controlled SQL transformations using dbt, SQLMesh or similar
- Experience with a cloud data warehouse, ideally Snowflake
- Experience with a modern BI/semantic-layer platform (Omni, Looker, Tableau or similar)
- Cross-functional collaboration
- Strong communication, including with senior leaders
- Problem solving and analytical judgment
- SQL
- dbt or SQLMesh
- Snowflake
Senior Data Analytics Engineer employer: Ronald James
Join a dynamic and innovative team as a Lead Back-end Engineer in a fast-scaling SaaS business, where your expertise will directly influence our technical direction. We foster a collaborative work culture that prioritises employee growth through continuous learning opportunities and mentorship, all while offering the flexibility of remote work. Enjoy competitive benefits and the chance to make a meaningful impact in a supportive environment that values your contributions.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Analytics Engineer
✨Get Involved in Data Science Meetups
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We think you need these skills to ace Senior Data Analytics Engineer
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Ronald James, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Ronald James. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Ronald James
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Ronald James!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
