Level

ASOS

Senior BI Engineer

ASOS is hiring a Senior BI Engineer in London, United Kingdom. Level rates it ; you can apply on Level.

AI in this role

Senior BI Engineer to mentor data teams, own data warehouses, and manage data feeds across FinTech and Fashion Tech.

databrickspythonpysparkdelta-laket-sqlpower-bimicrosoft-dynamics-365microsoft-fabric
bi-engineeringdata-warehousingdimensional-modelingmentoring

We're ASOS, the online retailer for fashion lovers all around the world. 

We exist to give our customers the confidence to be whoever they want to be, and that goes for our people too. At ASOS, you're free to be your true self without judgement, and channel your creativity into a platform used by millions. 

Everyone needs some help showing up as their best self. We're Disability Confident Committed - let our Talent team know if you need any reasonable adjustments throughout the recruitment process 

We’re looking for a Senior BI Engineer to work along with our BI team in FinTech and Fashion Tech. Reporting to the Staff Engineering Lead, you will take the strategy they set and turn it into delivery, leading the team day to day and being the senior, most experienced pair of hands on the data side.  

The team owns reporting and BI across all of FinTech and Fashion Tech. That covers the reports our business runs on, the reconciliations that keep our data feeds honest, and ownership of the data warehouse and the data sync between our ERP and the wider estate.  

Our stack is Python, PySpark, Delta Lake and Databricks, with T‑SQL, Kimball dimensional modelling and Power BI on top, working closely with Microsoft Dynamics 365 Finance and Operations data structures. We are currently reviewing whether to move from Databricks to Microsoft Fabric, so you should be comfortable working through a platform decision and the migration that may follow.  

Key Responsibilities  

Being Mentor to the BI Team  

  • Support the BI team day to day, turning the strategy set by the Staff Engineering Lead into a plan the team can deliver against.  

  • Support and mentor the other BI Engineers on both reports and the data side, through design reviews, pairing and code review.  

  • Be the senior technical voice in the team. Set the standards for how we model, build and test, and raise the bar on quality.  

  • Prioritise and balance the team’s work across reporting requests, reconciliations and platform work, and pick up the hardest builds yourself.  

Owning the Data Warehouse and Data Sync  

  • Own our data warehouse, including the dimensional model, the pipelines that load it and the standards that keep it consistent as it grows.  

  • Own the data sync between our ERP and the warehouse, making sure data lands completely, on time and in a shape the business can use.  

  • Build and maintain the reconciliations that prove our feeds are complete and accurate, and investigate and fix them when they break.  

Reporting and BI Delivery  

  • Deliver reporting our stakeholders trust, from the models underneath through to well built, performant Power BI reports.  

  • Design and build data pipelines in Python, PySpark and Delta Lake, and write the T‑SQL behind our models and reconciliations.  

  • Keep an eye on cost, performance and reliability across the platform, and keep improving what is already live.  

 

Working with Stakeholders  

  • Work with stakeholders across Finance, Tech and Fashion, including our Commercial, Buying and Product colleagues, to understand what they need from their data.  

  • Turn reporting requests into well shaped requirements, and challenge constructively when an existing report or a different cut of the data would do the job.  

  • Keep stakeholders updated on progress, priorities and any risks to the data they depend on, so there are no surprises.  

Working Across Tech  

  • Work closely with the solution, engineering and support teams across FinTech and Fashion Tech, so changes upstream in the ERP don’t break reporting downstream.  

  • Follow the wider ASOS delivery process, including governance, change control and release cadence, and run the team’s work through Azure DevOps.  

  • Work with Architecture, Security and Risk so what we build meets ASOS standards, protects sensitive financial data and stands up to audit.  

Why This Role Matters  

Almost every decision our Finance and commercial teams make rests on numbers this team produces, from month end close and supplier payments through to trading, stock and range performance. If the warehouse is wrong or a feed silently drops data, people make the wrong call.  

This role is where that quality is set. We need someone senior enough to own the warehouse and the ERP data sync end to end, lead a team through a possible platform move, and still be close enough to the detail to build the hard things themselves.  

 

Data and BI Experience  

  • Strong hands-on experience with Python, SQL, PySpark and Delta Lake for building scalable data pipelines.  

  • Experience across the Azure data stack, including Azure Data Factory (ADF), Azure Functions, Logic Apps and Azure Storage.  

  • Strong experience with Databricks and Microsoft Fabric, including Lakehouse and modern data engineering solutions.  

  • Strong SQL/T-SQL skills and experience with Kimball dimensional modelling and data warehouse design.  

  • Experience integrating ERP data, ideally Microsoft Dynamics 365 Finance & Operations or other major ERP platforms.  

  • Working knowledge of Power BI, DAX and data modelling, with a focus on delivering effective business reporting.  

  

Leadership  

  • Experience leading or mentoring other engineers, setting technical standards and lifting the quality of what a team produces.  

  • Comfortable taking a strategy someone else has set and turning it into a plan your team can deliver.  

  • Able to prioritise across competing requests and make a clear call on what gets done and what waits.  

Stakeholder Management and Rigour  

  • Confident with stakeholders across Finance, Tech and the commercial teams, able to explain data simply and push back when a request doesn’t stack up.  

  • A genuine eye for data quality, with the patience to chase a reconciliation break until you find the root cause.  

  • Organised and calm under pressure, particularly around month end and peak trading.  

  

We’d Also Love to See  

  • Experience of a lakehouse or warehouse migration, or of working through a platform decision such as Databricks to Microsoft Fabric.  

  • Knowledge of finance or supply chain processes such as procure to pay, order to cash, month end close or stock and warehouse operations.  

  • Experience in retail, ecommerce or fashion, particularly reporting for buying, merchandising or trading.  

  • Experience with CI/CD for data, testing frameworks, data observability or governance and cataloguing tools.  

Why You’ll Love This Role  

  • You will own the data warehouse and the ERP data sync for two of the most important areas of ASOS.  

  • It is a rare mix. You get to lead and mentor a team, set the technical standards, and still build the hard things yourself.  

  • A modern stack with a genuine platform decision ahead, and a real say in where we take it.  

  • Broad exposure across Finance, Commercial, Buying and Product, with work that visibly shapes how ASOS makes decisions. 

BeneFITS’ 

  • Employee discount (hello ASOS discount!) 
  • Employee sample sales 
  • 25 days paid annual leave + an extra celebration day for a special moment 
  • Discretionary bonus scheme 
  • Private medical care scheme 
  • Flexible benefits allowance - which you can choose to take as extra cash, or use towards other benefits 
  • Opportunity for personalised learning and in-the-moment experiences that enable you to thrive and excel in your role 

How we rate this

Senior BI Engineer at ASOS rates 10 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Bi EngineeringData WarehousingDimensional ModelingMentoringDatabricksPythonPysparkDelta Lake

Questions you could be asked

  1. Tell me about a project where bi engineering was part of your work. What did you do?
  2. Tell me about a project where data warehousing was part of your work. What did you do?
  3. Tell me about a project where dimensional modeling was part of your work. What did you do?
  4. Tell me about a project where mentoring was part of your work. What did you do?
  5. Walk me through how you've used Databricks in your day-to-day work.

Adapt your resume

  • List these exact terms on your resume: Bi Engineering, Data Warehousing, Dimensional Modeling, Mentoring, and Databricks. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.

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