At a Glance
- Tasks: Own and optimise our data and analytics stack, driving insights and AI adoption.
- Company: Swoon, a design-led brand revolutionising home trends with a modern data approach.
- Benefits: Competitive salary, share options, wellbeing allowance, and generous holiday perks.
- Other info: Fully remote work with opportunities for meet-ups and professional growth.
- Why this job: Gain autonomy in a dynamic role while making impactful decisions in a cutting-edge environment.
- Qualifications: Experience in building analytics stacks, strong SQL and Python skills, and AI fluency.
The predicted salary is between 63000 - 77000 £ per year.
Description
Swoon is an original, design-led brand using an innovative NPD process to discover the next home trends.
We run a lean team on a modern data stack - Snowflake, Airflow, Kleene, DBT and Sigma.
We're looking for an analytics engineer to own that stack end-to-end: how pipelines get built and maintained, how AI is used within them, how analysis reaches the exec team, and how the wider business self-serves answers.
What we’re looking for
This is a single-owner technical role.
You will own the warehouse, the transformation layer, the orchestration and the analytics surface the business consumes, and you will shape how they evolve.
No data team above you to escalate design decisions to.
You will partner closely with the commercial, marketing, and operations leads to turn their questions into insight that is actually executable.
That autonomy is the point. You need to be highly self-motivated, comfortable making architecture calls on your own judgement, and willing to fix problems rather than route them.
Key Responsibilities
- 1. Own the data stack
- Warehouse & modelling: Own the ELT process end-to-end - modelling, testing, documentation, cost and performance management.
- Orchestration: Own orchestration and ensure pipelines are reliable, timely, and accurate.
- Source integration: Maintain and extend extraction and loading from any new source.
- Data quality: Build the tests and checks that mean decisions aren't made on broken numbers.
- 2. Own the analytics stack
- BI layer strategy: Own the decision on how Swoon delivers analytics.
Assess whether our current BI layer is the right long-term solution.
You will be expected to recommend Swoon's BI future with evidence and own the consequences.
- Self-service: Further improve our self-serve analytics for our non-technical colleagues across commercial, operations and marketing to get answers without routing every question through you.
- 3. Drive AI adoption
- AI in the data workflow: Use AI tooling to compress the cost of analysis, transformation development, documentation and QA.
Review the current standard and where it can't be trusted.
- AI enablement across the business: Work with function leads to identify where AI removes manual work - ops reconciliation, customer service triage, content generation, supplier admin - and build or specify the tooling.
You are the technical enabler.
Requirements
- Track record: Demonstrable experience building and running a production analytics stack. Strong SQL and Python skills, plus Snowflake and orchestration (Airflow or equivalent).
- AI fluency: Hands-on experience using AI tools in a real workflow.
- Self-direction: You set your own roadmap, prioritise against commercial impact, and deliver without supervision.
- Communication: You can explain a technical constraint to a non-technical stakeholder and push back on a bad request without damaging the relationship.
Benefits
Compensation
- Competitive salary
- Share options programme
- Profit share scheme
- Wellbeing allowance
- Generous pension scheme
- Private medical cover for you and your family
- Holidays, working environment and other perks
- 27 days holiday rising to 30 with tenure
- Four months of summer hours finishing at 1 PM on a Friday
- Free furniture on each anniversary of employment
- Friends & family discount of 20%
- Fully remote working
- Frequent meet-ups, in-person workshops and socials
Analytics Engineer employer: Swoon Editions
Swoon is an exceptional employer that fosters a dynamic and innovative work culture, perfect for those looking to make a significant impact in the finance sector. With a focus on employee growth and development, you will have the opportunity to lead a talented finance team while enjoying the flexibility of remote work with just one day of travel to London each week. Our commitment to affordability and collaboration with leading retailers creates a unique environment where your contributions directly influence our ambitious growth trajectory.
StudySmarter Expert Advice🤫
We think this is how you could land Analytics Engineer
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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!
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Craft a Tailored Cover Letter:For a full-time role at Swoon Editions, 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 Swoon Editions. 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 Swoon Editions
✨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 Swoon Editions!
✨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.
