At a Glance
- Tasks: Create clean, tested data sets and enhance reporting capabilities with innovative solutions.
- Company: Join Butternut, a sustainable company passionate about dogs and data.
- Benefits: Competitive salary, flexible work options, and a supportive team environment.
- Other info: Collaborative culture focused on innovation and career growth.
- Why this job: Make a real impact on data-driven decisions while working with a fun-loving team.
- Qualifications: Experience with dbt, SQL, and BI tools; strong problem-solving skills.
The predicted salary is between 28800 - 48000 £ per year.
We’re hiring a mid weight Analytics Engineer to join our data team at Butternut. In this role, you will work closely with our business intelligence analysts to create clean, tested, well-documented, and well modelled data sets. Your work will be key in enabling both our data team and business users across the business, so you’ll feel the impact of your work quickly. You will actively contribute to enhancing our reporting capabilities by building robust systems that prioritise integrity and reliability. Additionally, you will play a role in developing a self-serve analytics approach, empowering more team members at Butternut to conduct independent analysis. Your focus will be on constructing and maintaining foundational data models using dbt, forming the backbone for data science and analytics at Butternut. If you are passionate about addressing challenges head on, fostering innovation, and contributing to data-driven decision-making, this might be the role for you.
Responsibilities
- Working with in-house product engineering teams to ensure modelling of source data meets downstream requirements.
- Maintaining and developing SQL data transformations in dbt.
- Defining best practices for data modelling, whilst also advising data analysts on how best to write data transformations.
- Working with stakeholders across the business to surface clean, intuitive datasets in our BI tool (we use Looker).
- Working with our in-house data team (analysis and science) to identify areas needing optimisation or more automation.
*Please note that this is not an exhaustive list, but rather intended as an indication of what your day to day might look like here at Butternut.*
A bit about you
- You have experience using dbt to build production-grade data models and test suites.
- You bring an engineering mindset to data (our data team sits within the software engineering department).
- Excellent SQL skills, including a solid understanding of how to optimise query performance.
- Good practical understanding of version control and git.
- Experience with BI tools, ideally Looker.
- You have technical expertise regarding data models and database design development.
- You have natural curiosity and a keen eye for detail.
- You can break down and explain complex processes, requirements and data concepts to both technical and non-technical stakeholders.
- You are a team-player who can work effectively within technical and with non-technical stakeholders to understand requirements.
- It would be a bonus if you have experience with Looker and the Looker API.
- Python coding skills, particularly in the areas of automation.
You can be sure you are joining a sustainable company who care about our people, product and our impact on the environment. Our goal is to help dogs live healthier, happier and longer lives whilst leaving humans smiling after every interaction.
Analytics Engineer employer: Butternut Box
At Butternut, we pride ourselves on being an exceptional employer that values innovation, collaboration, and personal growth. Our vibrant work culture fosters a supportive environment where you can thrive as an Analytics Engineer, contributing to meaningful projects that enhance our data capabilities while making a positive impact on the lives of dogs and their owners. With opportunities for professional development and a commitment to sustainability, you'll find a rewarding career path in a company that truly cares about its people and the planet.
StudySmarter Expert Advice🤫
We think this is how you could land Analytics Engineer
✨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 Butternut Box!
✨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 Butternut Box.
✨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 Butternut Box.
✨Apply Directly through Our Website
When you find a suitable opening like Analytics Engineer at Butternut Box, 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
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 Butternut Box, 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 Butternut Box. 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 Butternut Box
✨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 Butternut Box!
✨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.
