At a Glance
- Tasks: Develop analytics solutions to empower business users with trusted insights for decision making.
- Company: Join Canopius, a forward-thinking company transforming data into actionable insights.
- Benefits: Enjoy hybrid working, competitive salary, and opportunities for professional growth.
- Other info: Collaborate in a dynamic team environment with excellent career advancement potential.
- Why this job: Be at the forefront of data innovation and make a real impact in the industry.
- Qualifications: Experience with Power BI, SQL, and a passion for analytics engineering.
The predicted salary is between 63000 - 77000 £ per year.
Job Description
The Role
At Canopius, our delivery teams are responsible for ensuring that business users can effectively harness data insights to drive strategic decision making.
Our data strategy is centred around an enterprise Lakehouse platform on Databricks, avoiding fragmented, ungoverned silos on legacy technologies that hamper creativity and scalability.
We are building a governed, interoperable data estate that enables self-service for our business teams and provides the trusted foundation for advanced analytics, machine learning and AI to accelerate change across our industry.
This role is an opportunity to apply and develop your expertise in analytics engineering, data modelling and visualisation to build, extend and maintain the analytics and reporting capabilities that are central to decision making across Canopius.
You will contribute to business transformation projects, working closely with colleagues across Data and with business stakeholders, and using modern technologies such as Power BI and Databricks to deliver trusted, accessible insight.
The ideal candidate is an analytics engineer looking for a new challenge who is enthusiastic about using technology to improve how insight is delivered and consumed.
You should be able to understand business problems, translate them into clear requirements and deliver reliable solutions tailored to our needs, while applying good analytics engineering practices and seeking guidance where appropriate.
You should be comfortable collaborating and working as part of a dynamic multi-disciplinary team.
This role supports delivery of Canopius’ data strategy by helping to turn a governed, interoperable data estate into trusted, self‑service insight.
Alongside hands‑on development, the role will contribute to the transition of legacy reporting onto modern platforms and help ensure that analytics solutions are well designed, documented, supportable and aligned to agreed team standards.
Hybrid Working
We operate a hybrid working policy, combining the flexibility of home working with regular time together in the office.
For this role, you will be expected to work 2–3 days per week from our Manchester city centre office.
Responsibilities will include
- Develop analytics engineering and reporting solutions that help business users access trusted insight and make informed decisions.
- Work with business stakeholders, Product Owners, Business Analysts and other Data colleagues to understand information needs and translate them into clear, deliverable requirements.
- Design, build and maintain semantic models, datasets and reporting solutions using Power BI, paginated reports and Databricks, applying agreed team standards and development practices.
- Support report and dataset performance improvement by reviewing data models, DAX calculations, queries and refresh approaches, escalating more complex optimisation needs where required.
- Apply data validation, reconciliation and testing approaches to ensure analytics outputs are accurate, reliable and aligned to approved sources.
- Document solutions clearly, including data sources, logic, refresh schedules, access requirements and support considerations.
- Follow team standards for modelling conventions, naming, testing, deployment and version control, contributing suggestions for improvement where appropriate.
- Support the rationalisation and redevelopment of legacy reporting solutions as part of their migration onto modern platforms.
- Communicate analytics outputs, assumptions, risks and limitations clearly to both technical and non-technical audiences.
- Plan and manage assigned work items, producing realistic estimates, highlighting dependencies and raising risks or blockers early.
- Participate in peer review, knowledge sharing and team ceremonies, giving and receiving constructive feedback to improve solution quality.
- Use modern analytics engineering practices, automation opportunities and AI‑assisted tools where appropriate to improve delivery quality and efficiency.
- Keep abreast of developments and trends in data, analytics and reporting technology.
- Manage own task list and ensure that plans and priorities are agreed.
- Undertake other ad‑hoc duties as required.
Skills and Experience
- Hands‑on development experience with Power BI, including DAX, tabular/semantic models and paginated reports.
- Good understanding of analytics engineering principles, semantic/dimensional modelling and cloud‑based data platforms.
- Experience building clear, reliable and user‑friendly reports and dashboards that support business decision making.
- Good SQL skills for querying, analysing and transforming data.
Familiarity with Azure Dev Ops, Git and development lifecycle practices, including peer review, testing and deployment processes.
- Experience working in an Agile or Scrum environment and contributing effectively within cross‑functional teams.
- Analytical and problem‑solving skills with good attention to detail and a continuous improvement mindset.
- Good communication skills, with the ability to explain analysis, assumptions and solution choices clearly to technical and non-technical audiences.
- Experience with AI‑assisted development tools and copilots to improve productivity and delivery outcomes is advantageous.
- Familiarity with Tabular Editor and Databricks is desirable.
- Familiarity with specialty (re)insurance or Lloyd’s market data such as bordereaux, delegated authority, underwriting and claims is advantageous.
- #J-18808-Ljbffr
Analytics Engineer in Manchester employer: Intact Insurance (previously RSA)
At Intact Insurance, we are redefining the insurance landscape with a focus on simplicity, responsiveness, and community impact. As a Financial Lines Underwriting Leader, you will thrive in a collaborative environment that prioritises your growth and well-being, offering flexible working arrangements, generous benefits, and a commitment to diversity and inclusion. Join us to lead a dynamic team, build strong broker relationships, and make a meaningful difference in the industry while enjoying a fulfilling career path.
Contact Details:
Intact Insurance (previously RSA) Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Analytics Engineer in Manchester
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Intact Insurance (previously RSA)!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Analytics Engineer at Intact Insurance (previously RSA).
✨Leverage Professional Networks
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 Intact Insurance (previously RSA).
✨Apply Directly through Our Website
When you find a suitable opening like Analytics Engineer at Intact Insurance (previously RSA), make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Analytics Engineer in Manchester
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 Intact Insurance (previously RSA), 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 Intact Insurance (previously RSA). 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 Intact Insurance (previously RSA)
✨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 Intact Insurance (previously RSA)!
✨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.