AM

Amazon · amazon.jobs · checked today

Data Engineer, Amazon Music, Amazon Music Finance

Amazon Music is an immersive audio entertainment service that deepens connections between fans, artists, and creators. From personalized music playlists to exclusive podcasts, concert livestreams to artist merch, Amazon Music is innovating at some of the most exciting intersections of music and culture. We offer experiences that serve all listeners with our different tiers of service: Prime members get access to all the music in shuffle mode, and top ad-free podcasts, included with their membership;

Skills, with evidence

• Airflow / orchestration
  Construct resilient and scalable data pipelines using SQL/PySpark/Airflow to ingest, process, and transform substantial data volumes from diverse sources into a structured format, ensuring data quality and integrity.must havewrong?
• Data modelling
  Develop data models to support business intelligence, delivering actionable insights and interactive reports to end-users.must havewrong?
• Python
  Construct resilient and scalable data pipelines using SQL/PySpark/Airflow to ingest, process, and transform substantial data volumes from diverse sources into a structured format, ensuring data quality and integrity.must havewrong?
• SQL
  Construct resilient and scalable data pipelines using SQL/PySpark/Airflow to ingest, process, and transform substantial data volumes from diverse sources into a structured format, ensuring data quality and integrity.must havewrong?
• Warehousing
  Devise and implement an efficient, scalable data warehousing solution on AWS, utilizing appropriate NoSQL/SQL storage and database technologies for both structured and unstructured data.must havewrong?
• AWS
  Engage in collaborative efforts with cross-functional teams — data scientists, business intelligence engineers, and Finance Managers — to architect a state-of-the-art data analytics platform on AWS using the AWS Cloud Development Kit (CDK).must have · not practised herewrong?
• Machine learning
  Enable advanced analytics, machine learning, and generative AI capabilities within the platform, extracting predictive and prescriptive insights through tools like EMR and SageMaker.must have · not practised herewrong?
• Spark
  Enable advanced analytics, machine learning, and generative AI capabilities within the platform, extracting predictive and prescriptive insights through tools like EMR and SageMaker.wrong?
• Cost & performance
  Continuously monitor and optimize the performance of data pipelines, databases, and applications, ensuring low-latency data access for analytics and machine learning tasks.wrong?
• Data quality
  Construct resilient and scalable data pipelines using SQL/PySpark/Airflow to ingest, process, and transform substantial data volumes from diverse sources into a structured format, ensuring data quality and integrity.wrong?
• Failure handling
  Construct resilient and scalable data pipelines using SQL/PySpark/Airflow to ingest, process, and transform substantial data volumes from diverse sources into a structured format, ensuring data quality and integrity.wrong?
• Streaming
  - Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissionswrong?
• Governance & security
  Implement robust security measures and ensure data compliance with internal requirements, industry standards, and regulations to safeguard sensitive information.not practised herewrong?