Senior Data Engineer

About Reverb

Reverb is the largest online marketplace dedicated to buying and selling new, used, and vintage musical instruments. Since launching in 2013, Reverb has grown into a vibrant community of buyers and sellers all over the world. By focusing on inspiring content, price transparency, musician-focused e-commerce tools, a music-savvy customer service team, and more, Reverb has created an online destination where the global music community can connect over the perfect piece of music gear.

We love working at Reverb because we’re making the world more musical—through our marketplace and through Reverb Gives, which provides musical instruments to youth music education programs. We were named a “Best Place to Work” by Built in Chicago and a “Top Workplace” by the Chicago Tribune.

Our Engineering organization takes pride in crafting extraordinary software in service of our mission. We take an active role in product ownership by measuring the impact of features we release, collaborating with internal partners, fixing bugs, and ultimately building products and features that have a measurable impact on the business. Our team works together, pairing on design and coding patterns, peer-reviewing code, and elevating other developers through continuous mentorship and learning opportunities.

As part of Reverb’s Data Engineering team, you’ll help build a platform to enable confident, informed decisions and products that scale along with our business. We are a small, forward-thinking team looking for creative engineers who can face a wide range of problems, researching and implementing innovative solutions that make the most of our data.

• Maintain and improve our data pipelines and warehouse to ensure our users have timely access to accurate data. Our current stack uses Python, Airflow, Redshift, dbt, Looker, and more.
• Actively contribute to building out our machine learning platform by partnering with our Data Science, Search Science and Product teams who are focused on launching ML models for search, recommendations, and other areas.
• Collaborate with data analysts and other internal partners across the organization to find exciting insights within our data and make them available to our product teams.
• Build and share a deep understanding of your chosen languages, framework, or other area of expertise. Push yourself and the team to be continuously learning and growing.
• Own initiatives end-to-end, from clarifying business requirements and designing scalable data solutions to building robust testing, monitoring, and validation frameworks that uphold the highest standards of data quality.
• Lead and participate in pairing sessions, code reviews, and other team habits.

We use a wide variety of languages, frameworks, and databases, so many skills and experiences would make you a good fit for our team, including:

• Advanced experience with Python in data engineering, web and/or ML applications, with the ability to guide best practices and architectural decisions.
• Ownership of ETL/ELT pipelines and data platforms, including designing, scaling and improving data warehouse solutions.
• Expertise in relational databases, including data modeling, performance, optimizations, and crafting SQL queries.
• Strong understanding of different types of data storage and their trade-offs, with the ability to evaluate tools and influence technical direction.
• Experience designing and operating event-driven systems, including technologies such as Apache Kafka.
• Experience in machine learning techniques, pipelines, and applications.
• Proven ability to mentor and coach engineers, providing technical guidance, code reviews, and support for career growth.
• Demonstrated leadership in cross-functional collaboration with engineering peers, data scientists, data analysts, and other business and product partners.
• Solid experience with AWS infrastructure.

Remote-eligible roles (as…