At a Glance
- Tasks: Own analytics projects, design dashboards, and ensure data quality for impactful insights.
- Company: Fast-growing healthtech company focused on clinical innovation and data-driven solutions.
- Benefits: Flexible remote work, competitive salary, and opportunities for professional growth.
- Other info: Collaborative culture with influence over product direction and team growth.
- Why this job: Make a real difference in healthcare by shaping analytics that improve patient outcomes.
- Qualifications: Strong SQL skills, experience with Snowflake, and ability to mentor others.
The predicted salary is between 63000 - 77000 £ per year.
A Senior Analytics Engineer opportunity has opened up with a fast-growing, mission-driven healthtech company operating at the intersection of clinical innovation and data. If you're someone who thrives on building dependable data products and shaping the analytics function of an organisation doing genuinely meaningful work, could this be the role you've been looking for?
The Role
The Senior Analytics Engineer will take ownership of a broad analytics remit, spanning data warehouse development, pipeline reliability, business intelligence, and customer insight. You'll design and maintain transformation models, define key company metrics, and create dashboards and reports that help both internal teams and customers make smarter use of data. Day-to-day, you'll monitor and troubleshoot pipeline and data quality issues, support commercial systems including CRM platforms and workflow tooling, and partner with stakeholders across Sales, Marketing, and Operations to translate business questions into clear, validated analysis. There's real scope here to influence how the analytics platform evolves and to help set engineering standards as the team grows.
The Company
This is a UK-based healthtech business with a strong research heritage and a growing presence in both domestic and international markets. The company develops software used by healthcare providers to improve clinical awareness and patient outcomes, and it operates with a genuinely collaborative culture where individual contributors have real influence over the direction of the product and the team. Working arrangements are flexible and predominantly remote, with regular in-person sessions to support collaboration and planning.
What experience does the Senior Analytics Engineer need?
- Substantial experience in a data-focused role, including time operating at a senior or lead level, with strong SQL skills and a solid track record of building well-structured analytical models.
- Experience with cloud data warehousing (Snowflake, BigQuery, or equivalent), a strong grasp of data governance and platform security, and the ability to lead technically and mentor others within a growing engineering function.
- Hands-on experience with dbt or comparable modern transformation frameworks, plus Python applied to data integration, automation, or pipeline work, alongside experience managing production pipelines and CI/CD processes.
- A demonstrable ability to work closely with stakeholders, turning business questions into clear dashboards, reports, and validated analysis using tools such as Tableau, Streamlit, or similar BI platforms.
- Administration, integration, or workflow improvement across different commercial platforms, including CRM systems.
Senior Analytics Engineer, SQL, Python, Snowflake employer: Corriculo
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StudySmarter Expert Advice🤫
We think this is how you could land Senior Analytics Engineer, SQL, Python, Snowflake
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Corriculo.
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We think you need these skills to ace Senior Analytics Engineer, SQL, Python, Snowflake
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 Corriculo, 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 Corriculo. 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 Corriculo
✨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 Corriculo!
✨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.
