Apple Ads is looking to solve exciting business problems by delivering data solutions that help people find what they're looking for and help advertisers grow their businesses, while respecting user privacy and delivering value for advertisers of all sizes.
Requirements
- 4+ years of industry experience building scalable data pipelines and data platforms
- Strong computer science and data engineering fundamentals
- Expertise in programming languages such as Python/Java/Scala/Rust
- Expertise in NoSQL datastores (e.g. Cassandra, Keyspaces, ElastiCache)
- Expertise in relational databases and SQL
- Expertise in distributed systems and data processing technologies (e.g. Spark, Kafka, Flink)
- Expertise in access management , building catalogs , query engines
Responsibilities
- Design, develop, and optimize distributed algorithms and data processing frameworks
- Implement scalable feature pipelines to ingest, clean, transform, and analyze massive datasets
- Solve complex problems with multilayered data sets, and optimize existing machine learning libraries and frameworks
- Ensure data integrity, security, and compliance across all solutions
- Participate in cross-functional Agile teams to prototype and deliver impactful, data-driven products
- Build tools to integrate the data eco system
- delivering data solutions that solve exciting business problems
Other
- You will have the opportunity to define, refine, and refactor approaches, designs, and architectures to meet the data engineering challenges we must solve.
- You will join a team of world-class data engineers with an appetite for applying leading-edge technologies to deliver extraordinary experiences to our customers.
- You will play a meaningful role building data products that deliver on Apple's privacy commitments and change the way advertising works with data.
- You will collaborate closely with the business to deliver relevant data and insight to inform our strategy and decisions.
- You should have 4+ years experience in data engineering roles, ideally within the ads or media space.
