Interested in disrupting the trillion-pound retail industry? We’re tackling one of the hottest and most challenging problems in Machine Learning: designing and building a personalisation system that understands fashion.
As a Data Engineer in the Dressipi team, you will be working closely with the Data Science and Recommendations teams, helping them implement and deploy algorithms in a scalable manner. You’ll proactively monitor the performance of our infrastructure, data architecture and deployment processes and design and implement improvements to them.
Our current stack comprises Ruby, Python, Java and a small amount of rust and utilises a wide range of AWS services. We’re always interested in trying new technologies or approaches.
We are looking for a versatile person who can display leader qualities and is enthusiastic to tackle new problems across the both the data architecture and infrastructure areas as we continue to push our technology forward.
We are not a traditional tech start-up; it is an exciting environment with a diverse group of people, combining the best talents in all disciplines.
Work with engineers to improve the efficiency of data queries and infrastructure for both offline and online use cases
Pinpoint and help resolve bottlenecks and inefficiencies across infrastructure, queries, implementation and algorithms.
Recommend and guide changes to infrastructure, choice of datastores, data architecture, deployment processes
Monitor performance of infrastructure to catch issues before they become a problem
Collaborate with colleagues from data science and engineering backgrounds
Bachelor’s, Master’s or PhD in a relevant field (computer science, data mining, machine learning, statistics, math, engineering)
Track record of identifying, diagnosing and resolving performance inefficiencies
Solid SQL knowledge
Experience with AWS services such as EC2, Cloudformation, RDS, Cloudwatch
Track record of automating and maintaining infrastructure
The tenacity to solve hard and diverse problems
The will and ability to pick up new technologies and approaches as required
Comfortable working in a fast paced, highly collaborative work environment
2 or more years of industry experience
Knowledge of postgres, redshift
Experience with ETL processes
Experience with ruby, python
Worked with recommender systems
Experience with deployment automation & devops (packer, chef etc.)
Please send your CV and any other additional information to email@example.com