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For this specific role, we’re unable to offer visa sponsorship, so you’ll need the right to work in the UK
Build and maintain SQL transformations, tests and documentation in dbt
Develop Python code to automate data workflows and integrate systems
Make clean datasets available through Looker and AI data analyst tools
Work with product engineering so source data supports downstream needs
Advise the team on maintainable, reliable data modelling practices
Building and maintaining SQL transformations, tests and documentation in dbt.
Developing Python code to automate data workflows and integrate systems.
Working with stakeholders across the business to make clean, intuitive datasets available through Looker and AI data analyst tools.
Working with our in-house product engineering teams to ensure source data supports downstream requirements.
Contributing to data modelling best practices and advising the team on how to write reliable, maintainable transformations.
Actively hiringFirst seen by us 6 days ago, still listed, and not a repost of an earlier posting.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 6
Similar jobs usually come down between day 6 and day 47.
From 1,409 similar postings that came down. Coming down is not always a hire.
1 open job
Open jobs by the week we first saw them, last 12 weeks.
Hiring recordAdd your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
A bit about data at Butternut: We’re hiring a mid-level Analytics Engineer to join our data team at Butternut. In this role, you'll work closely with our data analysts and data scientists to create clean, tested, well-documented and well-modelled datasets. Your work will support teams and projects across the business, from experimentation to production. Our data stack includes Snowflake for data warehousing, dbt for data transformation and testing, and Looker for business intelligence. We also use Python for automation and integrations, AWS for infrastructure, and GitHub for version control and CI/CD. You'll build and maintain foundational data models that support reporting, data science and self-serve analytics. You’ll have the opportunity to build next generation analytics using generative AI and agentic tools to help your colleagues across the business get more value from the data. Alongside this, you’ll use Python to automate workflows and improve the reliability and efficiency of our data systems, making it easier for colleagues to access and use data confidently.
Our data stack includes Snowflake for data warehousing, dbt for data transformation and testing, and Looker for business intelligence. We also use Python for automation and integrations, AWS for infrastructure, and GitHub for version control and CI/CD. You'll build and maintain foundational data models that support reporting, data science and self-serve analytics. You’ll have the opportunity to build next generation analytics using generative AI and agentic tools to help your colleagues across the business get more value from the data. Alongside this, you’ll use Python to automate workflows and improve the reliability and efficiency of our data systems, making it easier for colleagues to access and use data confidently. If you enjoy solving problems, building reliable systems and helping people make better decisions with data (and you love dogs), this might be the role for you.
- Building and maintaining SQL transformations, tests and documentation in dbt. - Developing Python code to automate data workflows and integrate systems. - Contributing to data modelling best practices and advising the team on how to write reliable, maintainable transformations.
- You have experience using dbt to build production-grade data models and test suites. - You have practical experience writing maintainable Python code for data processing, automation or integrations. - You bring an engineering mindset to data, with a focus on testing, documentation and maintainability.
- Working with our in-house product engineering teams to ensure source data supports downstream requirements. - Building and maintaining SQL transformations, tests and documentation in dbt. - Developing Python code to automate data workflows and integrate systems.
- You bring an engineering mindset to data, with a focus on testing, documentation and maintainability. - You have excellent SQL skills, including a solid understanding of how to optimise query performance. - You have a good practical understanding of version control and Git.
- Experience building and maintaining ETL or ELT pipelines. - Experience with AWS. - Experience with BI tools, particularly Looker, LookML or the Looker API.
👀 What we're looking for: - You have experience using dbt to build production-grade data models and test suites. - You have practical experience writing maintainable Python code for data processing, automation or integrations.
- Experience with AWS. - Experience with BI tools, particularly Looker, LookML or the Looker API. - Experience with generative AI or agentic tools, or an interest in learning how to use them safely to provide value from data.
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We file this job under Analytics Engineer, by the work the posting describes.
Analytics engineers turn raw warehouse data into clean, tested and documented tables that analysts and dashboards can rely on, often with dbt.
Expect strong SQL, data modeling, Git, and a warehouse such as Snowflake, BigQuery or Redshift.
A data engineer gets data into the warehouse; an analytics engineer shapes it once it is there and works closer to the analysts who use it.
The government has no code for analytics engineers, so these figures are for the closest group, database architects, the same group we use for data engineers.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
We believe dogs deserve the healthiest, most natural and tastiest meals - with none of the nasties. That’s why we make FRESHly prepared food, cooked just like you would at home and delivered direct to our customers in perfect portions. As a B-Corp certified company, you’re joining a sustainable business that genuinely cares about our people, our products and our impact on the planet. Our goal is simple: to help dogs live healthier, happier, and longer lives, while leaving humans smiling after every interaction.
We’ve come a long way since our co-founders (Kev & Dave), hand delivered the very first Butternut Box. Today, we feed hundreds of thousands of hungry dogs across the UK and Europe - but we won’t stop until we’re feeding dogs everywhere. To get there, we need a team of brilliant people who share that ambition to come and work for us.
A bit about data at Butternut: We’re hiring a mid-level Analytics Engineer to join our data team at Butternut. In this role, you'll work closely with our data analysts and data scientists to create clean, tested, well-documented and well-modelled datasets. Your work will support teams and projects across the business, from experimentation to production.
Our data stack includes Snowflake for data warehousing, dbt for data transformation and testing, and Looker for business intelligence. We also use Python for automation and integrations, AWS for infrastructure, and GitHub for version control and CI/CD.
You'll build and maintain foundational data models that support reporting, data science and self-serve analytics. You’ll have the opportunity to build next generation analytics using generative AI and agentic tools to help your colleagues across the business get more value from the data. Alongside this, you’ll use Python to automate workflows and improve the reliability and efficiency of our data systems, making it easier for colleagues to access and use data confidently.
If you enjoy solving problems, building reliable systems and helping people make better decisions with data (and you love dogs), this might be the role for you.
You can expect to get stuck into:
Working with our in-house product engineering teams to ensure source data supports downstream requirements.
Building and maintaining SQL transformations, tests and documentation in dbt.
Developing Python code to automate data workflows and integrate systems.
Contributing to data modelling best practices and advising the team on how to write reliable, maintainable transformations.
Working with stakeholders across the business to make clean, intuitive datasets available through Looker and AI data analyst tools.
Working with our analysts and data scientists to identify opportunities to improve data quality, optimise performance and automate manual processes.
(Please note that this is not an exhaustive list, but is intended to give you an indication of what your day-to-day might look like here at Butternut.)
You have experience using dbt to build production-grade data models and test suites.
You have practical experience writing maintainable Python code for data processing, automation or integrations.
You bring an engineering mindset to data, with a focus on testing, documentation and maintainability.
You have excellent SQL skills, including a solid understanding of how to optimise query performance.
You have a good practical understanding of version control and Git.
You have natural curiosity and a keen eye for detail.
You can explain complex processes, requirements and data concepts to both technical and non-technical stakeholders.
You work collaboratively with technical teams and business stakeholders to understand requirements and develop useful solutions.
It would be a bonus if you have:
Experience building and maintaining ETL or ELT pipelines.
Experience with AWS.
Experience with BI tools, particularly Looker, LookML or the Looker API.
Experience with generative AI or agentic tools, or an interest in learning how to use them safely to provide value from data.
We usually expect our interview process to take 3-5 weeks, end to end.
Our team thrives on collaboration. We spend 3 days a week in our West London office (Monday, Wednesday, and Thursday) and 2 days working from wherever you’re most productive. Because being together is a big part of our culture, we’re looking for someone within a comfortable commutable distance to London.
We’re a small (but mighty!) recruitment team. We aim to respond to everyone personally, but if we’re flooded with brilliant applications, we may need to close the role early. We appreciate your patience while we review applications.
For this specific role, we’re unable to offer visa sponsorship, so you’ll need the right to work in the UK.
Butternut Box is an equal opportunity employer. We believe that to make the best food for all dogs, we need a team that represents all humans. We celebrate different nationalities, backgrounds, experiences and perspectives. We are specifically committed to increasing representation from underrepresented groups. We want a strong, diverse team built from different identities and lived experiences. We’re not perfect, but we are dedicated to the ongoing work of building an inclusive, supportive place where you can do the best work of your career.
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London
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- We’re a small (but mighty!) recruitment team. We aim to respond to everyone personally, but if we’re flooded with brilliant applications, we may need to close the role early. We appreciate your patience while we review applications. - For this specific role, we’re unable to offer visa sponsorship, so you’ll need the right to work in the UK. ❗️We believe in a seat at the table for everyone.