We're looking for a Data Engineer who enjoys crafting reliable real-time data pipelines
We encourage applications from people who aren’t cis white men, who are currently over-represented on the engineering team at Thread.
You'll be a key part of Thread’s Data Science team, and you’ll have ownership over Thread’s data infrastructure. You’ll also work with people from product, styling, and other teams in our office in East London to build the features that will help people dress well, and in turn improve their self-confidence and happiness.
You’ll work closely with Ed Snelson, Thread’s Head of Applied Research, along with the rest of the tight-knit Data Science team who work on improving Thread’s core recommendation engine, as well as auxiliary data-science projects supporting the rest of the company. Using data to help our users dress well is at the core of what we do; it's not a nice-to-have bolted onto the product. You'll be responsible for building real-time machine-learning model training pipelines, improving our user-event pipeline, systems for deploying models to production, data warehousing, and generally ensuring Thread’s data infrastructure is top-notch, reliable, scalable and monitored so that the whole company can access the quality data they need.
You will work on…
- Ownership of data pipeline, maintaining, improving and scaling
- Developing interesting data architectures for real-time machine learning systems
- Architecting a user-feature-data store for supporting machine learning models in development/training and live in production
- Maintenance and growth of our initial data warehouse, working with others in the company to establish how this will be used in the near future, and build the infrastructure to get additional data-sources data into the warehouse
Our current data tech stack (which is open to change!):
- Mostly Python based, with a smattering of Scala
- An event pipeline built around Protobuf, FluentD, Kinesis, Redis
- BigQuery for data-warehousing
- Data job pipeline built with Luigi
You may be a fit for this role if you…
- Have worked on the setup, deployment and monitoring of a data pipeline
- Have experience working with real-time event-based pipelines
- Can write good code and know your way around web technologies such as Redis and relational databases
- Are experienced in devops and cloud services, as you’ll be deploying and maintaining the services that power data science at Thread
- Have worked with data job dependency pipelines such as Luigi and Airflow
- May have some experience of data warehousing and ETL workflows
- Care about uptime and performance of systems
- Have at least a basic interest of data science / ML and an interest in learning more
- Want to work in a team that values clear and empathetic communication
- Enjoy learning technologies that are new to you but are pragmatic in your choices when it comes to deciding what to use
- Want to share knowledge and experience, to improve the code quality, practices, and processes across the team
What is it like to work at Thread?
We have a relaxed working environment, and trust our employees to be productive on a schedule that suits them.
We have a flexible holiday policy and believe you should be able to take off the time you need, when you need it. Recently Thread employees have taken time off to spend half-term with their kids, taken a last minute long-weekend to go hiking, and taken a few days off to play video games and recuperate.
We are committed to a transparent working environment, and as a part of this all email that isn’t personal goes to mailing lists accessible by anyone on the team. Our founders and team leads take questions on any subject at a weekly all-hands meeting, and most importantly we try to cultivate a culture where asking questions is encouraged and where responses will be clear and meaningful.
We place a high value on learning and personal growth. Everyone has regular 1:1s with their managers to discuss how they want to develop, we give and receive 360 feedback to direct our growth and are encouraged to attend conferences and share resources that will help us develop new skills. On a company-level, we host biweekly Lunch & Learn sessions, run blameless 5 Whys whenever something goes wrong, have an all-company offsite twice a year to go deeper on improving how we work together, and conclude most projects with a retrospective to draw out any lessons on how to improve.
We have a considered approach to our compensation. Twice a year we survey the market for every role, and ensure that we are paying at the top end for a startup in London. As the market changes and as your role and experience develop, so will your compensation. This is important to us as we want to create a company that proactively rewards your growth and experience, rather than rewarding those most comfortable with asking for a raise.
Our culture is important to us and so we spend time every week as a company reflecting on various aspects of our culture and coming up with experiments to improve upon it, we frame our project retrospective discussions with our values, and we recognise those who have a positive impact on it. We haven’t got everything right, but with these practices we believe we’re on a path to having an effective and enjoyable culture.
If this role sounds exciting to you, please apply below. If you’re unsure, please still get in touch—we welcome applicants from different backgrounds and would love to hear from you.