At a Glance
- Tasks: Lead a team of Analytics Engineers to build scalable data foundations and drive analytics initiatives.
- Company: Join Compare the Market, a purpose-driven tech company transforming financial decision-making.
- Benefits: Enjoy a hybrid work environment, competitive salary, and opportunities for personal growth.
- Other info: Be part of a diverse team that values results and fosters continuous improvement.
- Why this job: Make a real impact in a fast-paced, innovative environment while developing your leadership skills.
- Qualifications: Experience in leading analytics engineering teams and advanced SQL skills required.
The predicted salary is between 70000 - 90000 £ per year.
Function: Data & AI Solutions
Location: Hybrid, London or Peterborough office
Curious about what’s next? So are we. Join Compare the Market and help to make financial decision making a breeze for millions. At Compare the Market, we’re a purpose-driven business powered by tech and AI. We’re building high-performing, results-driven teams with the skills, mindset, and ambition to deliver outcomes at pace. Every role here plays a part in driving our mission forward, and we create an environment where you can bring your authentic self, grow a truly characterful career, and see the direct impact of your work on the lives of our customers.
As the Analytics Engineering Manager, you will lead and grow a team of Analytics Engineers responsible for building scalable, trusted and reusable data foundations that power analytics, decision making and AI across Compare the Market. You’ll lead the execution of the Analytics Engineering strategy by translating organisational priorities into high quality data products, trusted semantic foundations and modern analytics capabilities.
Some Of The Great Things You'll Be Doing:
- Lead and support a team of Analytics Engineers, fostering a high performing, collaborative and inclusive team culture.
- Accountable for performance management, career development, engagement, retention, coaching and mentoring, ensuring engineers have clear growth pathways and opportunities to reach their potential.
- Build strong cross-functional relationships and work collaboratively with Product, Analytics, Technology, Platform and Data teams to identify priorities and deliver analytics engineering initiatives.
- Drive the design, evolution and stewardship of scalable, maintainable and analytics-ready data models, transformation pipelines and reusable data products using modern analytics engineering practices.
- Own the development and governance of trusted semantic foundations, ensuring consistent definitions of business metrics, entities and dimensions across analytics, reporting, self-service and AI use cases.
- Establish and maintain data contracts, lineage standards and governance controls that improve trust, traceability and change management across the data estate.
- Hold the team accountable for delivering high quality outcomes, meeting engineering standards and achieving agreed business objectives.
- Establish and uplift engineering standards across testing, documentation, CI/CD, observability and data quality.
- Define and implement data observability practices including monitoring, alerting and operational controls that improve reliability and consumer confidence in data products.
- Improve operational excellence across the analytics estate by reducing technical debt, streamlining workflows and improving developer experience.
- Lead delivery planning and execution across multiple initiatives, ensuring outcomes remain aligned to business priorities while balancing platform sustainability, innovation and delivery commitments.
- Drive adoption of self-service analytics capabilities by improving the accessibility, reliability and usability of trusted data products.
- Partner with Data Scientists and AI teams to ensure data products, semantic assets and model inputs are reliable, governed and fit for purpose for machine learning and AI-enabled solutions.
- Influence stakeholders at all levels across Product, Analytics, Technology and Data functions to align priorities, communicate trade-offs and manage delivery risks.
- Foster a culture of continuous improvement, psychological safety, accountability and knowledge sharing.
What We'd Like To See From You:
- Experience leading Analytics Engineering, Data Engineering or Business Intelligence Engineering teams within a modern data environment.
- Advanced SQL skills and hands‑on experience with dbt and modern analytics engineering practices.
- Proven experience designing and maintaining scalable data models, transformation pipelines and reusable data products.
- Experience establishing data quality, observability, lineage and governance practices within production environments.
- Experience designing or governing semantic layers, trusted metrics and reusable business definitions.
- Strong understanding of cloud-based data platforms and modern analytics ecosystems.
- Experience balancing technical strategy, platform improvement and delivery priorities across multiple stakeholders.
- Strong communication and influencing skills, with the ability to translate technical concepts for both technical and non‑technical audiences.
- Proven people leadership capability including coaching, performance management and talent development.
- Experience supporting AI, machine learning or advanced analytics use cases through trusted and well‑governed data foundations.
- Experience with data contracts, self‑service analytics platforms and modern data governance approaches.
- Familiarity with cloud data technologies such as BigQuery, Snowflake, Databricks or equivalent.
Why Compare the Market?
We’re a business built for pace and performance. Here, you’ll be encouraged to think differently, act boldly, and deliver brilliantly in a culture that values results and rewards progress. We believe diverse teams make better decisions, and we’re committed to creating an inclusive workplace where everyone feels empowered to grow, contribute, and thrive. If you’re ready to stretch yourself, raise the bar, and grow with a team that’s serious about performance, innovation, and purpose, we’d love to hear from you.
Analytics Engineering Manager in Peterborough employer: Compare the Market
At Compare the Market, we pride ourselves on being a purpose-driven employer that fosters a culture of innovation and collaboration. Our hybrid work model in London or Peterborough allows for flexibility while you lead a talented team of Analytics Engineers, driving impactful data solutions that enhance financial decision-making for millions. With a strong focus on employee growth, accountability, and inclusivity, we provide ample opportunities for career development and encourage you to bring your authentic self to work.
StudySmarter Expert Advice🤫
We think this is how you could land Analytics Engineering Manager in Peterborough
✨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 Compare the Market!
✨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 Engineering Manager at Compare the Market.
✨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 Compare the Market.
✨Apply Directly through Our Website
When you find a suitable opening like Analytics Engineering Manager at Compare the Market, 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 Engineering Manager in Peterborough
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 Compare the Market, 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 Compare the Market. 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 Compare the Market
✨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 Compare the Market!
✨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.
