Backend Engineer (Python)
Summary
Backend Engineer (Python) building a large-scale data pipeline that ingests millions of web activity events and runs attribution models for a B2B content marketing platform. Day to day involves Python and AWS services (Kinesis, S3, RDS), database tuning, scheduling algorithms, and a collaborative workflow with testing, pair programming and code reviews.
At the moment our team is working on developing a data pipeline that ingests millions of web activities and uses attribution models to give deep insights to marketers about their performance. There is some serious engineering behind making all of that work and we want to find people that love tackling hard problems like this head on. We are a very strong team of developers that are focused on helping each other to improve as engineers every day. We write automated tests as part of our development workflow, practice pair programming, perform peer code reviews, and share knowledge in weekly tech talks.
We have an amazing office overlooking the Boston Common with a kitchen full of snacks and weekly catered lunches and top market salary, equity package, 401k plan, Medical with 100% deductible reimbursement, dental and vision insurance and gym membership reimbursement.
Our ideal candidate:
- Has 2-5 years of experience working with large-scale data-intensive applications, with a preference to python.
- Has experience with AWS technologies such as Kinesis, S3 and RDS.
- Feels that testing is a core part of their development process.
- Has experience or familiarity working in a functional programming style or language.
- Enjoys working closely with other developers, pair programming, reviewing code and sharing ideas.
One day you might be developing smarter scheduling algorithms for syncing data from external sources, the next you could be tuning our database to reduce bottlenecks and the next you could be reviewing and refactoring code that is responsible for generating reports that hundreds of marketers rely on. We love people that thrive on solving tough problems with clean, well-tested and scalable code
