The Find My team is dedicated to building a seamless, private, and secure experience for users to locate their devices, personal items, and share location with friends and family. We're a group of highly motivated engineers, designers, and product managers who are passionate about creating a simple and reliable experience for hundreds of millions of users worldwide. We thrive in a fast paced environment where team members are often encouraged to wear multiple hats and contribute to various aspects of the product lifecycle. Innovation and creative problem-solving are at the heart of our team, and we constantly explore new approaches to deliver groundbreaking solutions while collaborating with diverse disciplines across the company, including hardware, software, and privacy, to deliver an exceptional user experience.

Description

As a Data Engineer on our team, you'll thrive in a fast-paced, startup-like environment, collaborating closely with a passionate cross-functional team to transform complex data into insights that power our shared mission. You'll be instrumental in designing and building the analytics pipelines behind exciting new features, and your contributions will directly impact millions of users. We embrace continuous iteration and improvement, so you'll have the opportunity to learn, grow, and refine your skills as we build the future of Find My. You will translate analytics needs from Data Science, Engineering, Product, and Program Management into high-quality, well-modeled data artifacts. Developing methods to monitor data quality and balancing competing priorities will be key to your success. You will dive deep into complex data engineering problems to ensure our solutions are extensible, reliable, and ready to deliver at scale.

Minimum Qualifications

BS in Computer Science, Data Engineering, or related field 3+ years of experience working with large data sets and dimensional data modeling 3+ years of experience with data processing using Spark and SparkSQL Familiarity with data pipeline orchestration tools Proficiency in Java or Scala, and experience with Python Experience with Amazon Web Services, GCP, or Azure Strong communication and collaboration skills

Preferred Qualifications

Experience with open table formats such as Delta Lake or Apache Iceberg Experience with Spark on Kubernetes Experience with data quality monitoring and anomaly detection Familiarity with BI/visualization tools (e.g., Superset) Familiarity with privacy-preserving data engineering techniques Experience with machine learning applied to the domain of data engineering and analytics

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Data Engineer, Find My

Description

Minimum Qualifications

Preferred Qualifications