At a Glance
- Tasks: Design and maintain data pipelines to turn marketing data into actionable insights.
- Company: Join Canon, a leader in tech innovation with a focus on customer-centric solutions.
- Benefits: Enjoy hybrid working, flexible hours, 25 days holiday, and discounts on Canon products.
- Other info: Collaborative environment with opportunities for professional development and career advancement.
- Why this job: Shape data solutions that drive growth and enhance customer experiences at Canon.
- Qualifications: 1 year as a data engineer or 3+ years as a data analyst; strong SQL skills required.
The predicted salary is between 63000 - 77000 £ per year.
Overview
As a Data Engineer, you will design, build, and maintain data pipelines and infrastructure in Google Cloud and Azure to support Canon’s ITCG marketing and CRM initiatives.
You’ll collaborate with cross-functional teams to integrate marketing, ecommerce and sales data, turning data into insights for leadership.
You’ll ensure data quality and scalable architectures while enabling data-driven decision making.
This role offers the chance to shape data solutions across marketing and CRM, contributing to Canon’s data-driven growth and customer focus.
- Pay / Benefits
- hybrid working (3 days in office, 2 from home)
- flexible hours
- professional development
- 25 days of holiday (plus up to 5 holiday purchase)
- pension scheme
- discount on Canon products up to 38%
Responsibilities
- Design, build, and maintain data pipelines, models, and visualisations that integrate marketing and sales data with other sources (Big Query, Power BI)
- Conduct exploratory analysis with SQL/Python/R to identify trends and opportunities and present findings to stakeholders
- Deliver BI reports and dashboards for Senior Leadership and cross-functional teams
- Develop and optimise data models for scalable storage and processing in Google Cloud and Azure
- Implement data quality checks and cleansing processes and collaborate with IT on upstream changes
- Analyze customer journeys across ECOM and Marketing B2C sites and identify improvements
- Key requirements
- 1 year experience as data engineer/architect or 3+ years as data analyst
- Excellent SQL skills
- Understanding of data warehousing, data modelling concepts, and structuring new data tables
- Experience or familiarity with data cleaning and data quality checks
- Bachelor’s degree
- Experience with Google Cloud Platform or Microsoft Azure (Big Query / data services) is advantageous
- Drive for results
- Customer focus
- Ownership and accountability
- SQL
- Data warehousing and data modelling
- Python or R for automation and integrations
Analyst - Data & Analytics in London employer: Canon
Canon is an exceptional employer, offering a dynamic work environment where innovation meets expertise in the graphic arts and production inkjet sectors. With a strong focus on employee growth, Canon provides comprehensive training and development opportunities, alongside a competitive salary and benefits package, including a 20% bonus and car allowance. The collaborative culture encourages problem-solving and customer engagement, making it an ideal place for professionals looking to make a meaningful impact in their field while enjoying the flexibility of a UK-based role with occasional travel.
StudySmarter Expert Advice🤫
We think this is how you could land Analyst - Data & Analytics in London
✨Get Involved in Data Science Meetups
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We think you need these skills to ace Analyst - Data & Analytics in London
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 Canon, 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 Canon. 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 Canon
✨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 Canon!
✨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.
