Senior Data Engineer, UnitedMasters

• We need someone who can help us maintain our current data pipelines right away, and over time, help us design our next generation of highly-scalable data solutions
• The ideal candidate pairs strong data engineering fundamentals with backend programming skills, and is excited to learn more about the unique domain that is the music industry
• Strong competency with SQL, Python
• Expertise in the technical processes core to data engineering (e.g., ETL, ELT, data modeling, relational databases, data replication, distributed systems), and knowledgeable about adjacent processes (domain modeling, application development, data science, product analytics)
• Expertise in Postgres-SQL, and postgres database tuning preferred
• Experience participating in the design and maintenance of cloud-based data systems that leverage AWS tools (RDS, S3, lambda, glue, Athena.)
• Can build and manage data pipelines that scale well, and has done so in a variety of environments/use-cases (e.g. pipelines for user-facing data, ML work, and internal analytics)
• Strong communication and collaboration skills; has a track record of working with cross-functional partners, can provide quality feedback in pull request reviews, and seeks out feedback from peers at all stages of the development process
• 3+ years of experience doing data engineering work at enterprise scale, or in a rapidly growing startup environment
• 5+ years writing production code in a professional setting

Desirable

• We are looking for a Sr. Data Engineer to join UnitedMasters!
• One of the most important services our app provides is in-depth analytics to artists on their streaming and social data
• This data also powers other business-critical data systems: internal tools for identifying high potential artists to partner with, streaming fraud identification systems, and more
• With our user base and stream volume increasing, so is the scale of data that we need processed
• Build SQL-based large-scale batch and real-time data pipelines using Snowflake, DBT, Airflow, AWS, and Postgres
• Partner with our product teams to turn music data feature ideas (for both the artist app, and internal A&Rs) into scalable, production-grade data systems that deliver real value
• Write python tools that help orchestrate data processing, and that automate common data engineering tasks
• Help maintain and extend our python-based analytics service layer, where the application interacts with our data pipeline outputs
• Scale your impact by mentoring software engineers on data engineering best practices, and "teaching them how to fish" for simpler tasks that require distributed data processing