Spotify

Senior Data Engineer, AdTech

Spotify

full-time

Posted on:

Location: New York • 🇺🇸 United States

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Salary

💰 $160,091 - $228,702 per year

Job Level

Senior

Tech Stack

AirflowApacheAWSAzureCassandraCloudDynamoDBETLGoogle Cloud PlatformGRPCJavaKafkaKotlinMySQLPostgresPythonScalaSparkSpringSpring BootSpringBoot

About the role

  • Our mission on the Advertising Product & Technology team is to build a next generation advertising platform that aligns with our unique value proposition for audio and video. The ads measurement team is dedicated to creating scalable, reliable data and backend systems that power our advertising ecosystem. We are seeking engineers who are passionate about designing, developing, and maintaining robust and scalable systems. You will work closely with cross-functional teams to build data services and APIs that support our advertising platform, enabling innovative features and analytics. Positioned at the heart of our backend operations, you will assist product teams in driving high performance, reliability, and scalability across our systems. Our team culture emphasizes creative problem-solving, rapid iteration, execution, and collaboration.

Requirements

  • Proven experience in backend and data engineering, with a balanced skill set in both domains or open to mastering both domains. Strong programming skills in languages such as Java, Python, Scala, or Kotlin. Hands-on experience with cloud platforms like GCP, AWS, or Azure. Familiarity with API design, microservice architecture, and frameworks like Spring Boot or gRPC. Knowledge of data processing frameworks such as Apache Beam, Scio, or Spark. Experience with database systems, both relational (e.g., PostgreSQL, MySQL) and non-relational (e.g., Cassandra, DynamoDB). Proficiency with orchestration tools like Airflow and streaming tools like Kafka or Pub/Sub. A commitment to agile software development practices, CI/CD, and test-driven development. Excellent problem-solving skills with a passion for optimizing both systems and data pipelines.
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