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- Tasks: Lead the Data Engineering team and manage the analytics pipeline for a top fashion platform.
- Company: Join a leading fashion-tech company with over 150M annual shoppers.
- Benefits: Enjoy 29 days off, private healthcare, and a generous training budget.
- Why this job: Shape the future of fashion shopping through innovative data solutions.
- Qualifications: Experience in Python, AWS, and mentoring engineers is essential.
- Other info: Dynamic work environment with opportunities for personal and professional growth.
The predicted salary is between 48000 - 84000 £ per year.
Fashion-Tech, London
About my client:
They are the definitive fashion shopping website and app, used by over 150M shoppers a year to discover and buy fashion. More than 8.5M products from over 12,000 brands and stores can be accessed through their website and app, offering shoppers convenience and unparalleled choice. This is a great opportunity should you be looking to work in small, self-managing, autonomous teams with end-to-end responsibility for a specific customer-focused project.
About the Role:
They are looking for a Lead Data Engineer to head up our Data Engineering team in the Infrastructure tribe. You will be responsible for managing and growing the analytics pipeline that’s used by every team in the company to join together all of the data. You will help to set the structure for data events, manage the infrastructure and software that teams depend on to shuffle events into the data lake, liaise with engineers throughout the company on their needs for the pipeline, help maintain the tooling and developer experience of what you build, and manage the Data Engineering team. You will also be responsible for helping shape and enforce their data governance policies that ensure events are built against and adhering to a defined schema, develop data models that heuristically analyze and warn against issues with data quality, and help to coordinate the rectification of any data problems through the development of monitoring and alerting that allows the engineering teams to own and self-serve their event pipelines.
Main Responsibilities:
- The analytics pipeline: building and maintaining the necessary infrastructure to move and process event data from where it’s created or ingested and into our data lake.
- Working in Python on top of the AWS technology stack: utilising Kinesis, Firehose, Lambda, S3 and Glue to deliver events into Snowflake for reporting on by our BI teams.
- Using infrastructure-as-code in Terraform to create and maintain scalable infrastructure to support our data lake pipelines.
- Driving our data engineering chapter to liaise with other data engineers throughout the company to gather feedback and ideas for development of the analytics pipeline.
- Cultivate a great developer experience that engineers can use both locally and in production to build and maintain events in our pipeline.
- Create processes to help engineers monitor and improve data quality and integrity.
- Perform analysis to troubleshoot and fix data and infrastructure related issues and provide recommendations for improving the pipeline to help avoid problems.
- Investigate the modelling of data events to proactively identify data quality issues and find ways to autonomously introduce this feedback into production workflows.
About You:
- Interest in data pipelines, analytics and event handling, and building the necessary infrastructure.
- Experience supporting and mentoring other engineers and working directly with them to achieve career growth.
- Able to work comfortably with the Python code and AWS infrastructure that powers our pipeline.
- Experience of technical problem solving and troubleshooting and incident management.
- Able to triage and manage the project workload for the team in a structured but flexible kanban-style process.
- The ability to work in a supportive but autonomous environment: you’ll be expected to take stakeholder direction to develop well thought-out solutions but with the ability to have your own input on direction.
What do they offer:
- You get 29 days’ time off throughout the year to take a well-earned rest, in addition to the 8 public bank holidays.
- As a fashion company they give you £250 to spend on the site in Year 1, £500 in Year 2, £750 in Year 3 and £1000 from Year 4 onwards.
- Private Healthcare by Vitality.
- Conferences and events.
- They are big on learning, so all employees are allocated an individual training & development budget of £1,000.
- Enhanced family leave entitlements for both parents and carers.
- Discounted eye tests and glasses.
- Team meet-ups, social events, sports and exercise events.
- Cycle-to-work scheme.
- Transport season ticket loans.
Please forward a copy of your most recent CV to the following email address and an initial call will be scheduled.
Lead Data Engineer in London employer: hire|py
Contact Detail:
hire|py Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Data Engineer in London
✨Tip Number 1
Network like a pro! Reach out to people in the fashion-tech industry on LinkedIn or at events. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data engineering projects, especially those involving Python and AWS. This will give potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on common data engineering challenges. Be ready to discuss how you’ve tackled issues with data quality and infrastructure in the past.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive!
We think you need these skills to ace Lead Data Engineer in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the Lead Data Engineer role. Highlight your experience with Python, AWS, and data pipelines to show us you're the right fit!
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about data engineering and how you can contribute to our team. Share specific examples of your past work that align with the responsibilities listed in the job description.
Showcase Your Problem-Solving Skills: In your application, mention instances where you've tackled technical challenges or improved data quality. We love seeing how you approach problem-solving, especially in a collaborative environment!
Apply Through Our Website: We encourage you to submit your application through our website for a smoother process. It helps us keep track of your application and ensures you don’t miss out on any updates from us!
How to prepare for a job interview at hire|py
✨Know Your Tech Stack
Make sure you’re well-versed in the AWS technology stack mentioned in the job description, especially Kinesis, Firehose, Lambda, S3, and Glue. Brush up on your Python skills too, as you'll likely be asked to demonstrate your coding abilities or discuss past projects involving these technologies.
✨Showcase Your Leadership Skills
As a Lead Data Engineer, you’ll need to manage and mentor other engineers. Prepare examples of how you've successfully led teams or projects in the past. Think about specific challenges you faced and how you helped your team overcome them.
✨Understand Data Governance
Familiarise yourself with data governance policies and practices. Be ready to discuss how you would enforce these policies and ensure data quality within the analytics pipeline. This shows that you not only understand the technical side but also the importance of data integrity.
✨Prepare for Problem-Solving Questions
Expect to tackle technical problem-solving scenarios during the interview. Practice explaining your thought process clearly and logically when troubleshooting issues. Use examples from your experience to illustrate how you’ve approached similar challenges in the past.
