At a Glance
- Tasks: Transform complex data into actionable insights and build scalable data pipelines.
- Company: Join a leading automotive data solutions team with a focus on innovation.
- Benefits: Enjoy competitive pay, hybrid work, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on autonomy and technical excellence.
- Why this job: Make a real impact on strategic products and drive data-driven decisions.
- Qualifications: Strong SQL and Python skills, experience with modern data tools.
The predicted salary is between 63000 - 77000 £ per year.
Join Cox Automotive Europe’s Data Solutions team, where data sits at the heart of everything we do—from powering our Decision Engine platform to delivering vehicle intelligence and commercial insights across the business.
As an Analytics Engineer, you’ll operate at the intersection of data engineering, analytics, and data science, helping turn complex data into robust, production-ready datasets and pipelines. You’ll play a critical role in enabling faster decision-making, improving model performance, and driving innovation across multiple high-impact workstreams.
What You’ll Be Doing
- Build & Power Data Products
- Design and maintain scalable data pipelines supporting pricing, channel, and timing recommendation models
- Create reusable datasets and dbt models to accelerate analytics and product delivery
- Enable experimentation through A/B testing infrastructure and performance analysis
- Shape Vehicle Data Intelligence
- Develop enriched datasets across multiple European markets (e.g., France, Italy, Spain, Belgium)
- Integrate internal and third-party data sources (auction, RPI, and more)
- Support pricing, benchmarking, and valuation analytics capabilities
- Enable Data Science at Scale
- Collaborate with Data Scientists to productionise models and automate feature engineering
- Own the critical layer between raw data and model inputs
- Ensure data quality, lineage, and reproducibility across pipelines
- Drive Platform Excellence
- Work within a modern Databricks-based data platform
- Contribute to data governance, lineage, and documentation
- Partner with engineering and architecture teams on shared data initiatives
What We’re Looking For
- Essential Skills
- Strong SQL and Python experience
- Hands‑on experience with modern data tooling (e.g., Databricks, dbt)
- Proven ability to build and maintain data transformation pipelines
- Solid understanding of data modelling principles
- Ability to translate complex business problems into reliable data solutions
- Experience working in a commercial or product-driven data environment
- Strong communication skills—able to engage technical and non-technical stakeholders
- Nice to Have
- Experience with automotive, marketplace, or pricing data
- Exposure to machine learning workflows and feature engineering
- Familiarity with experimentation and A/B testing frameworks
- Knowledge of data governance, lineage, and cataloguing
- Experience with Agile tools (Jira, Rally, etc.)
Why Join Us?
- Be part of a high‑performing, 15‑person Data Solutions team working across product, data science, and platform disciplines
- Work on high‑visibility, strategic initiatives with real commercial impact
- Collaborate closely with senior stakeholders across product and data science
- Enjoy a culture of autonomy, curiosity, and technical excellence
Your Impact
This is a rare opportunity to shape the data foundations behind key strategic products. Your work will directly influence pricing decisions, product development, and the evolution of our data platform.
Analytics Engineer in Manchester employer: Stryker Corporation
Stryker Corporation is an exceptional employer that fosters a dynamic and inclusive work culture, offering employees the chance to thrive in a remote setting while being part of a leading medical communications team. With a strong emphasis on professional development and growth opportunities, employees are encouraged to enhance their skills and advance their careers, all while contributing to meaningful projects that impact healthcare globally.
StudySmarter Expert Advice🤫
We think this is how you could land Analytics Engineer in Manchester
✨Get Involved in Data Science Meetups
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✨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 Stryker Corporation.
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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 Stryker Corporation.
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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 Stryker Corporation, 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 Stryker Corporation. 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 Stryker Corporation
✨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 Stryker Corporation!
✨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.
