Join our dynamic team as a Lead Senior Data Engineer, a pivotal role within the Music Supply Chain, focusing on optimizing workflows for music publishing and recorded music businesses. This position involves end-to-end management from acquisition and distribution to monetization, driven by insightful data analytics. We seek a curious and efficient engineer eager to influence development direction and collaborate with top talent in an agile, team-oriented environment.

You will be instrumental in shaping the Music Repertoire, planning, distribution, and sales operations. Your focus will be on robust data streams and seamless integrations across various internal and external systems. This role demands close collaboration with multiple teams to design, implement, and maintain scalable and accurate data integration capabilities, ensuring operational efficiency throughout the music supply chain.

As a Lead Software Engineer, you will architect and deliver resilient, scalable systems for our music supply chain applications. This role combines hands-on technical leadership with strategic input, translating business needs into innovative solutions.

You will lead architectural design and implementation for large-scale projects, ensuring technical excellence and alignment with organizational standards. Mentoring senior engineers and facilitating cross-functional collaboration with Product, QA, and Design teams will be key. You will own and lead development projects, setting architectural direction and ensuring scalability and maintainability, with decisions significantly impacting project and team outcomes.

Your impact will extend across product and project success, contributing to customer and operational objectives. You will regularly drive innovation and technical strategy, ensuring broad influence on business outcomes.

We are looking for an experienced software engineer with at least 7 years of proven experience in designing and delivering production-grade applications. Strong proficiency in Python is essential, alongside hands-on experience with Apache Spark for large-scale data processing, supporting file formats like Avro, Parquet, and JSON.

Advanced SQL skills are required, encompassing data modeling, schema design, relational database concepts, query optimization, and performance tuning. Expertise in data platform technologies such as Databricks and Snowflake, coupled with orchestration frameworks like Apache Airflow, is crucial. A deep understanding of data integration concepts and ETL/ELT pipeline design is also necessary.

Experience with containerization (Docker, Kubernetes), DevOps practices (GitLab, CI/CD), and cloud environments like AWS is vital. Familiarity with data lakehouse and microservices architectures, along with API integration (RESTful, GraphQL) and messaging frameworks (Kafka, Kinesis), is expected. Proficiency in Linux environments and shell scripting, alongside a strong grasp of object-oriented and functional programming paradigms, is required. An understanding of data governance, security, and observability best practices is also a must. Excellent communication, collaboration, and problem-solving skills are paramount for success in this role, alongside strong time management and organizational abilities within Agile environments.