The MissionSwoon is an original, design-led brand utilising an innovative NPD process to discover the next home trends. As we expand our footprint across the UK's leading retailers, we are moving away from manual data management toward a highly automated, AI-driven trading model. We are seeking a technical, data-native graduate to own our partner uploads for John Lewis, Next, and M&S. You do not need years of corporate experience for this role. Instead, we want raw analytical drive. You will build the automated data pipelines to ensure our listings are flawless, and you will leverage AI to ensure they actually sell.What we are looking forThis is a dual-impact graduate role combining robust data automation with forward-thinking digital merchandising.On one hand, you are a spreadsheet wizard and automation enthusiast. You look at manual data formatting and see an opportunity to write a script, build a macro, or deploy an advanced formula to eliminate human error entirely. You have an obsessive attention to detail and believe that clean data is the foundation of good business.On the other hand, you possess deep intellectual curiosity about e-commerce growth. You do not want a product to just be visible on a website, you want to understand exactly why it sells, or more importantly, why it doesn't and how to optimise it. You are excited about using AI and analytics tools to track visibility, analyse competition and use data-driven insights to maximise our performance on partner platforms.RequirementsResponsibilities1. Data Automation and Partner IntegrationAutomated Uploads: Own the end-to-end data preparation and upload process for major retail partners (John Lewis, Next, and M&S), transforming raw internal product data into platform-ready formats.Pipeline Engineering: Move us away from manual data entry by building and maintaining robust, automated data pipelines using Python, SQL, and advanced Excel to validate, transform, and deliver partner-ready product data at scale.Rigorous Data Quality Assurance: Act as the final gatekeeper for product data. Implement foolproof validation checks to ensure zero errors in pricing, dimensions, SKUs, and imagery before sheets are submitted to partners.Partner Troubleshooting: Serve as the technical point of contact for partner portal errors, quickly diagnosing and resolving feed or upload discrepancies.2. AI Merchandising and Digital Shelf OptimisationVisibility Tracking: Deploy and manage AI-driven tools (we use Claude) to monitor Swoon’s actual visibility and search rankings on partner websites.Conversion Optimisation: Drive performance rather than just pushing listings live. Analyse how our products are displayed, identify optimisation gaps like missing search terms or poor imagery placement, and optimise copy to drive sales.Competitor Intelligence: Use AI and analytics tools to benchmark our digital shelf presence against competitors, identifying emerging trends and structural gaps in partner ranges.Commercial Feedback Loop: Translate partner sales data and visibility metrics into actionable insights for the Design teams, ensuring we double down on what moves the needle.Who You AreYou are a recent graduate with a numerate or analytical degree discipline — Economics, Mathematics, Computer Science, Data Science, Physics, or similar. You do not need to be a software engineer, but you should be comfortable writing code to solve problems.Desirable skills and experience include proficiency in Excel at an advanced level (XLOOKUP, INDEX/MATCH, dynamic arrays), working knowledge of Python for data manipulation and automation, and a foundation in SQL for querying structured datasets. Familiarity with modern analytics tools is a plus — we use Snowflake and Sigma, which means you will be working with a genuinely current data stack rather than legacy tooling.You are commercially curious, detail-obsessed, and motivated by outcomes rather than activity. You want to understand what drives partner sales performance, not just keep the lights on.Team and LearningYou will sit alongside our Data and Trading teams, working closely with both on a daily basis. This is a role with real mentorship built in — you will learn how a fast-moving ecommerce business makes commercial decisions, and you will have direct input into those decisions from day one. For the right candidate, the trajectory from this role is significant.Working Hours, Location and FlexibilityHours: 9:00am to 5:30pm, Monday to Friday. We have flexibility for Friday pm off if you work extra hours Monday to Thursday.Remote-First: Most of the time you will be working remotely from home within the UK.Collaborative Workshops: We require travel to London a few times per month for workshops, and all UK train travel for these sessions will be fully expensed.BenefitsCompetitive salaryShare options programmeBonus schemeWellbeing allowancePension scheme (including employer contribution)Private medical cover for you and your family25 days of annual leave + an extra day for each year of tenureYour birthday off + an additional day for volunteering/community workFree furniture on each anniversary of employmentFriends & family discount
The Mission
Swoon is an original, design-led brand utilising an innovative NPD process to discover the next home trends. As we expand our footprint across the UK's leading retailers, we are moving away from manual data management toward a highly automated, AI-driven trading model. We are seeking a technical, data-native graduate to own our partner uploads for John Lewis, Next, and M&S. You do not need years of corporate experience for this role. Instead, we want raw analytical drive. You will build the automated data pipelines to ensure our listings are flawless, and you will leverage AI to ensure they actually sell.
What we are looking for
This is a dual-impact graduate role combining robust data automation with forward-thinking digital merchandising.
On one hand, you are a spreadsheet wizard and automation enthusiast. You look at manual data formatting and see an opportunity to write a script, build a macro, or deploy an advanced formula to eliminate human error entirely. You have an obsessive attention to detail and believe that clean data is the foundation of good business.
On the other hand, you possess deep intellectual curiosity about e-commerce growth. You do not want a product to just be visible on a website, you want to understand exactly why it sells, or more importantly, why it doesn't and how to optimise it. You are excited about using AI and analytics tools to track visibility, analyse competition and use data-driven insights to maximise our performance on partner platforms.
Requirements
Responsibilities
1. Data Automation and Partner Integration
- Automated Uploads: Own the end-to-end data preparation and upload process for major retail partners (John Lewis, Next, and M&S), transforming raw internal product data into platform-ready formats.
- Pipeline Engineering: Move us away from manual data entry by building and maintaining robust, automated data pipelines using Python, SQL, and advanced Excel to validate, transform, and deliver partner-ready product data at scale.
- Rigorous Data Quality Assurance: Act as the final gatekeeper for product data. Implement foolproof validation checks to ensure zero errors in pricing, dimensions, SKUs, and imagery before sheets are submitted to partners.
- Partner Troubleshooting: Serve as the technical point of contact for partner portal errors, quickly diagnosing and resolving feed or upload discrepancies.
2. AI Merchandising and Digital Shelf Optimisation
- Visibility Tracking: Deploy and manage AI-driven tools (we use Claude) to monitor Swoon’s actual visibility and search rankings on partner websites.
- Conversion Optimisation: Drive performance rather than just pushing listings live. Analyse how our products are displayed, identify optimisation gaps like missing search terms or poor imagery placement, and optimise copy to drive sales.
- Competitor Intelligence: Use AI and analytics tools to benchmark our digital shelf presence against competitors, identifying emerging trends and structural gaps in partner ranges.
- Commercial Feedback Loop: Translate partner sales data and visibility metrics into actionable insights for the Design teams, ensuring we double down on what moves the needle.
Who You Are
You are a recent graduate with a numerate or analytical degree discipline — Economics, Mathematics, Computer Science, Data Science, Physics, or similar. You do not need to be a software engineer, but you should be comfortable writing code to solve problems.
Desirable skills and experience include proficiency in Excel at an advanced level (XLOOKUP, INDEX/MATCH, dynamic arrays), working knowledge of Python for data manipulation and automation, and a foundation in SQL for querying structured datasets. Familiarity with modern analytics tools is a plus — we use Snowflake and Sigma, which means you will be working with a genuinely current data stack rather than legacy tooling.
You are commercially curious, detail-obsessed, and motivated by outcomes rather than activity. You want to understand what drives partner sales performance, not just keep the lights on.
Team and Learning
You will sit alongside our Data and Trading teams, working closely with both on a daily basis. This is a role with real mentorship built in — you will learn how a fast-moving ecommerce business makes commercial decisions, and you will have direct input into those decisions from day one. For the right candidate, the trajectory from this role is significant.
Working Hours, Location and Flexibility
- Hours: 9:00am to 5:30pm, Monday to Friday. We have flexibility for Friday pm off if you work extra hours Monday to Thursday.
- Remote-First: Most of the time you will be working remotely from home within the UK.
- Collaborative Workshops: We require travel to London a few times per month for workshops, and all UK train travel for these sessions will be fully expensed.
Benefits
- Competitive salary
- Share options programme
- Bonus scheme
- Wellbeing allowance
- Pension scheme (including employer contribution)
- Private medical cover for you and your family
- 25 days of annual leave + an extra day for each year of tenure
- Your birthday off + an additional day for volunteering/community work
- Free furniture on each anniversary of employment
- Friends & family discount
