Software, Data Engineer (Music Solutions)
Hundreds of millions of users. Billions of Shazams. Countless moments of discovery. Shazam brings a unique brand of magic to millions every day. It’s our people - their imagination, skills and ideas - that shape our future, and help us make the impossible come to life.
At Shazam, we are fortunate to have some of the most exciting data in the music world and beyond.
As a Software, Data Engineer (Music Solutions), you will play a pivotal role in solving complex problems related to music grouping and categorisation. You will be working with large datasets, leveraging your expertise in DevOps, Data Engineering, and possibly AI/ML to build robust data-driven solutions. Your work will ensure that our systems are scalable, reliable, and efficient, supporting millions of users worldwide.
The role is based in London while involving close collaboration with cross-functional teams in various locations to integrate data solutions.
You will work across a wide array of systems & technologies that include both batch & real-time pipelines.
You will design, develop, and maintain scalable data pipelines and infrastructure to process large volumes of music-related data.
You will implement map-reduce, clustering and classification algorithms to improve music grouping and categorisation.
You will monitor and troubleshoot pipeline performance, ensuring high availability and correctness of results
You will utilise Hadoop, Spark, BigQuery and other big data technologies to manage and analyse large datasets.
Employ cloud technologies, particularly GCP, to optimise data processing and storage
- Continuous learning and improvement mindset, willing to push yourself outside of your comfort zone
- Excellent problem-solving skills, attention to detail, and a collaborative mindset
- Experience with DevOps practices and tools such as CI/CD, Docker, and Kubernetes
- In-depth knowledge of distributed computing including Hadoop and Spark.
- Strong programming skills in languages such as Python, Java, or Scala.
- Good knowledge about the music domain, and processing audio signals
- Interest or experience in clustering large datasets and working with graph databases
- Not afraid to work with multiple programming languages such as C++, and JVM based languages.
- Interest or experience in managing GCP infrastructure via Terraform, plus working with other cloud technologies
- Familiarity with AI/ML methodologies and frameworks like TensorFlow, PyTorch, or Scikit-learn, etc.
- Experience in orchestrating jobs using tools such as Airflow, Luigi