Data Analytics Engineer - Apple Services Engineering

As a member of the Apple Games App Data Engineering team, you will have significant responsibility and influence in shaping its strategic direction. This is a software engineering position. We write robust code, not just ad-hoc scripts. Our software processes dozens of terabytes of gaming and player engagement data on a daily basis. Our jobs and applications must be efficient, scalable, and stable. Although we write software, data is our main product and first-class citizen. We care about accurate and qualitative data as much as we care about fine, clean, and manageable code. The data we produce powers Apple leadership and our game developer partners with insights about player behavior, new innovations, and the next big things in gaming. You will play a key role in developing analytics solutions tailored specifically for game developers, leveraging your knowledge of the third-party gaming analytics ecosystem to help build best-in-class tools. To succeed here you will need to be a proponent of building world-class analytical solutions. To be a part of the team means we will want your ideas, concerns, and opinions in our discussions. We are highly collaborative. You will collaborate closely with engineering, product, and partner organizations. Privacy is a foundational engineering requirement in everything we build, and our solutions are designed to comply with Apple's privacy principles from the ground up. Our team is small and focused, where engineers work across a broad range of problems. Minimum Qualifications Bachelor's Degree in Computer Science, Engineering, or equivalent related experience Experience building analytics and data solutions specifically for game developers. Familiarity with third-party analytics tools and platforms used in the gaming industry. 5+ years of hands-on experience building distributed data processing applications using Apache Spark or Apache Flink. 5+ years of programming experience in Scala (preferred) or Java. Experience with Big data: Hadoop, HDFS, Spark, SQL, Kafka. Proven skills in designing scalable, highly available distributed systems using technologies like Kafka, Iceberg, Kubernetes, Airflow, and Cassandra. Preferred Qualifications Good understanding of software engineering principles and fundamentals including algorithms and data structures. Self-directed, self-motivated, and ability to create architecture and design documents. Ability to capture cross-functional requirements and translate them into practical engineering tasks. Excellent communication skills and proven ability to work in a cross-functional environment.