Lyst is a search and discovery platform which connects millions of shoppers globally with the world’s leading fashion designers and stores, giving them a simpler, more engaging buying experience. We work in small, self-managing, autonomous teams with end-to-end responsibility for a specific customer-focused project. This structure brings together Lysters from all the disciplines that are needed to deliver the squad’s goals. We reward these squads for the impact they make and value the innovative approaches that autonomy and alignment can bring. We hire great people and get out of their way.
We are looking for a Data Engineer on the Bidding & Attribution team who can help build the data pipelines, infrastructure and tooling needed to train and deploy our machine learning models.
- Communication: You are able to communicate clearly and be humble when sharing ideas with everyone on the team.
- Commitment to quality: You strive to write code that is readable by everyone, well tested and robust in production.
- Motivation: You understand and are motivated by the challenge of building scalable, reliable distributed systems.
- Experience with data processing in the cloud: You have experience working with large amounts of remotely hosted data and developing tools and infrastructure needed to process this.
- Knowledge of Machine Learning: You are interested in modern machine learning pipelines and are keen to work in this area and learn more.
- You will also be experienced using traditional relational databases (e.g. Postgres) and have good intuition for how to write efficient SQL queries.
- You will have excellent Python knowledge and experience and be up to date on best Python practices.
What will you be working on?
- Data engineering: Designing the Extract, Transform and Load pipeline to process data from our data warehouse / data lake into a form suitable for training machine learning models.
- Backend systems: Working across all backend systems to ensure the data we need is gathered and stored in our data lake, and also writing the backend systems to train and serve models.
- Full stack: Some full stack work to enable our main website to be able to query and use the ML model predictions in real time.
- Analytics, Reporting and Monitoring: Developing reports and dashboards to monitor both the training and prediction performance of our models.
- We work mainly in Python, running on a range of AWS technologies such as S3, ECS, SQS, Glue, Sagemaker and Postgres RDS, along with non-AWS tools such as Snowflake, CircleCI, Docker and Github.
- We have high engineering standards and practice comprehensive testing, code reviews, continuous integration and continuous deployment across all engineering teams.
Things that matter to us:
You are pragmatic and you like engaging with hard engineering problems.
You like all things about data, passing it around, parsing it, storing it and reporting on it.
You are curious at heart and like to take ownership of something to make it better.
You are a team player and communicate with your peers and other stakeholders in the company on a day to day basis
Being confronted with a difficult or strange problem makes you feel like a detective that wants to crack the mystery.
You enjoy nurturing your colleagues and empowering the team to the fullest of their ability.
- You get 29 days’ time off throughout the year to take a well earned rest. There’s also the 8 public bank holidays too
- Private Healthcare by Vitality. Your health is important to us which is why we offer all employees a comprehensive healthcare scheme from the day you start
- The Lyst Clothing Benefit. We're a fashion company, so we'll 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. You're going to look fantastic!
- Conferences and events. We’re big on learning and development, so all Lysters get £1500 to spend on courses and training
- Discounted eye tests and glasses
- Team meet-ups, social events, sports and exercise events
- Cycle-to-work scheme
- Childcare vouchers
- Transport season ticket loans
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