We are looking for a data engineer that will build data-driven solutions to deliver podcast experiences to our 170+ million active users by analysing our on-platform usage data, understanding our data from an off-platform perspective and improving the accuracy and precision of our data and related recommendations. Above all, your work will impact the way the world experiences podcasts.
What you’ll do
- Continuously design, develop, and test data-driven solutions
- Work with state-of-the-art data processing frameworks and technologies
- Improve data quality through testing, tooling and continuously evaluating performance
- Collaborate with backend software engineers, ML experts and others
- Work in cross-functional agile teams to regularly experiment, iterate, and deliver on new product objectives with an end-to-end responsibility for your team’s mission
- Work from our office in Boston, Massachusetts
Who you are
- You have experience architecting and operating large data pipelines
- You know how to work with high volume heterogeneous data with distributed systems such as Hadoop and Google Cloud Platform
- You have experience with one or more higher-level JVM-based data processing frameworks like Beam, Dataflow, Crunch, Scalding, Storm, and Spark (not just Pig/Hive/BigQuery/other SQL-like abstractions)
- You are knowledgeable about data modeling, data access, and data storage techniques
- You care about agile software processes, data-driven development, reliability, and responsible experimentation
- You are passionate about creating clean code and have a strong foundation in coding and building data pipelines
We are proud to foster a workplace free from discrimination. We strongly believe that diversity of experience, perspectives, and background will lead to a better environment for our employees and a better product for our users and our creators. This is something we value deeply and we encourage everyone to come be a part of changing the way the world listens to music.