At a Glance
- Tasks: Lead analytics engineering, transforming data into self-serve insights for the whole company.
- Company: Join Kato, a fast-growing PropTech startup revolutionising commercial property.
- Benefits: Competitive salary, 25 days leave, extra life days, and enhanced parental leave.
- Other info: Casual dress code, snazzy offices, and a culture that values diversity and innovation.
- Why this job: Shape the future of analytics in a dynamic startup environment with real impact.
- Qualifications: Experience in SaaS startups, dbt architecture, and BI tools like Tableau or Power BI.
The predicted salary is between 56700 - 69300 £ per year.
Kato is a fast-growing Prop Tech company, backed by top-tier VCs, investors, and industry experts.
Our mission is to revolutionise commercial property through our all-in-one online platform and extensive industry data.
We’re just getting started and are seeking dynamic, confident individuals to join our journey and help shape the future of commercial property.
Role overview
As Senior Analytics Engineer working in the Data Platform team, you will own the analytics engineering discipline at Kato, shaping the modelling layer that turns our extensive industry data into trusted, self-serve analytics for the whole business.
You'll bring strong hands-on technical capability, experience modelling complex domains, and the people skills to successfully educate and promote analytics across the business.
You'll continuously raise the bar for analytics practice at Kato, with the scope to shape the discipline as our data function scales.
- Expected to raise the bar for data analytics at Kato - setting the standards we build to, and making our data accessible to everyone in the business.
- Expected to translate key business questions into durable, self-serve data assets rather than one-off answers.
- Expected to enable the definition and consistency of core business metrics.
- Responsible for data governance across the modelling layer; quality controls, testing, monitoring, lineage and documentation.
- Responsible for the reliable operation of the transformation layer - troubleshooting failures and reducing their recurrence.
- Responsible for the architecture and workflow of the data modelling layer.
- Responsible for the data contracts either side of the modelling layer; stable interfaces for downstream consumers, managed change from upstream sources.
- Expected to apply software engineering practice to analytics code; version control, automated testing and continuous integration as a default rather than an aspiration.
- Expected to embrace AI assistance throughout your workflow, staying current with developments and experimenting with new technologies as they become available.
Experience & skills
We’re committed to building a diverse team with a variety of backgrounds and experiences. The following skills and experiences will help you succeed in this role:
- You have worked in a Saa S start up or scale up environment before and are used to identifying and removing ambiguity.
- You have designed, built and run dbt architecture in production, with CI/CD.
- You have worked with Databricks (preferred) or a comparable cloud data platform.
- You have enabled self-serve analytics with BI tools such as Quick Sight, Tableau or Power BI.
- You can work under pressure and multi-task alongside managing expectations of your work.
- You are an effective communicator and pro-actively share your knowledge and skills.
We want to ensure a great fit for both you and us, so we look for a few key qualities in all our team members:
- Excited for each step of the journey you are about to embark on
- Up for the challenge of a startup environment which is on a growth trajectory
- Strong work ethic and the ability to work as part of a team
- Adaptable to new and different challenges and ways of working
- Pro‑active, keen to take ownership of your work and responsibilities
- Bring a positive attitude and show empathy to your colleagues and customers
- Tech-forward; your instinct is to use technology to solve problems wherever you see them
- Keep it simple; right sizing your solutions to fit the business context
- We’re asking a lot of you, so it’s only fair that we give something back:
- A competitive salary and bonus
- 25 days annual leave plus extra “life” days; a duvet day, a life-event day, your birthday off
- Enhanced maternity and paternity leave policy
- Training & support provided
- Enrolment in our company pension plan
- Casual dress code
- Snazzy offices with free snacks and drinks
- #J-18808-Ljbffr
Senior Analytics Engineer employer: Kato
At Kato, we pride ourselves on being an exceptional employer that fosters a culture of growth, creativity, and collaboration. Our hybrid work model allows for flexibility while ensuring meaningful in-person interactions, and our commitment to employee development is reflected in our comprehensive training programmes and supportive environment. With competitive salaries, generous leave policies, and a vibrant office atmosphere in London, Kato offers a unique opportunity to be part of a transformative journey in the commercial property sector.
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We think this is how you could land Senior Analytics Engineer
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We think you need these skills to ace Senior Analytics Engineer
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!
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Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Kato. 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 Kato
✨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!
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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
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✨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.
