Since launching in 2013, Reverb has grown into the world’s most popular music gear site, connecting millions of people around the world to the gear and the inspiration they need to make music. Our growing team comes to work each day to make Reverb the best place for musicians and music lovers to buy, sell, and learn about music gear.
As part of the Reverb Data Engineering team, you’ll help build the platform to enable data-driven decisions and products that scale along with our business. We’re using Python and Scala to build a streaming architecture to support production machine learning. We’re a small, eager team so we’re looking for engineers who can take a high degree of initiative and enjoy working across team boundaries.
Everyone at Reverb takes creative initiative, helps set their own priorities, and comes up with new ways to grow the business. Our engineers take pride in building great software but take even more pride in shipping great features for our customers. If want to learn more, check out this video on working at Reverb
- Design, build and maintain our data pipeline and machine learning services.
- Develop ETL ecosystem tools (currently using Elasticsearch, Spark, Python, Redis, PostgreSQL, and more)
- Collaborate with data science and stakeholders across the organization to raise the bar for data best practices and management
- Demonstrate and communicate a deep understanding of your chosen languages and frameworks to be able to make tradeoffs. Able to do more with less complexity.
- Advocate for internal and external customers to break down problems, set priorities and follow up on performance and functionality
- Build and maintain internal data processing and visualization tools to ensure that stakeholders have timely access to data.
- Lead in pairing sessions, code reviews and take initiative on research projects/ requirements
- Professional experience in high-volume ETL systems. Python experience a must, Scala and AWS experience are pluses as they're part of our ecosystem.
- Understands different types of data storage and their trade-offs with regards to availability, consistency, read/write throughput and maintenance cost.
- High-level understanding of machine learning techniques such as regression, data cleaning and/or clustering algorithms.
- Able to communicate effectively with engineering peers, data analytics, and business stakeholders.
What you'll get:
- Competitive salary and stock options in a high growth company.
- No-bureaucracy environment where ownership and initiative is valued.
- Health insurance and a healthy work environment-- no 80 hour weeks.
- 401k with 4% match.
- Flexible vacation and sick days.
- A MacBook Air, monitor, keyboard, mouse of your choice and standing desk.
- Discounts on music gear.
This is a local position in Chicago, please no remote workers or recruiters. Please send us a link to your Github!