SoundCloud empowers artists and fans to connect and share through music. Founded in 2007, SoundCloud is an artist-first platform empowering artists to build and grow their careers by providing them with the most progressive tools, services, and resources. With over 400+ million tracks from 40 million artists, the future of music is SoundCloud.
We’re looking for a Senior Data Engineer to join our Data Platform team, which is responsible for the efficient, reliable, secure, and compliant propagation of all datasets across the company to our data warehouses. At SoundCloud, we rely heavily upon data-driven, informed decision making, and the Data Platform team is key to enabling that.
Key Responsibilities:
The Data Platform team cooperates mostly with infrastructure engineering on the back-end side, taking care of all the integrations, and builds software to make the data flow from the source into the data warehouse or the system which transforms data in real time. As a Data Engineer at SoundCloud, you will be experienced in designing and implementing highly scalable, distributed, real-time data pipelines and developing highly scalable and secure data services in languages like Go and Scala and Java. We also use Google Cloud Platform (DataFlow, BigTable, AI Platform, BigQuery, Kafka, Kubernetes, Spark, Airflow, Terraform).
Experience and Background:
The ideal candidate will have 3+ years of experience in back-end engineering including 1-2 years of experience setting up data processing pipelines, ideally in the cloud environment (GCP)
Experience designing and implementing (real-time) data processing systems, facilitating technical decisions, considering technical tradeoffs
You are a strong individual contributor driven by solving challenging technical problems
You are comfortable participating in architecture discussions, planning new and improving existing solutions
You are comfortable with large scale data infrastructure (PBs scale). You understand the tradeoffs that come with itNice-To-Have
Experience with Cloud Migrations
Experience deploying ML models in production
Experience with DevOps tools and technologies
