Data & Analytics Engineer, AiDP

Imagine what you could do here. At Apple new ideas have a way of becoming extraordinary products services and customer experiences very quickly. Bring passion and dedication to your work and theres no telling what you could u0026 Data Platforms (AiDP) is ISu0026Ts engine for AI-powered innovation. The team brings together data application development and machine learning including generative AI along with data services and customer success functions to help ISu0026T build solutions more efficiently and streamline the adoption and embedding of generative AI across Apple.n

The Developer Experience Platform team is building the next generation of AI-powered tools that accelerate how applications are developed across Apple. We are looking for a Data u0026 Analytics Engineer to help design build and scale the data foundation that powers this this role you will develop robust data pipelines and analytics systems that enable AI agents autonomous workflows and data-driven insightsdirectly impacting how software is built at scale.

As a hands-on engineer you will:nnDesign build and maintain scalable data pipelines and ELT workflows to support AI and analytics use casesnDevelop clean reliable and well-modeled datasets for both batch and real-time consumptionnPartner closely with AI/ML engineers and platform teams to deliver high-quality data for model training inference and agent workflowsnImplement data quality observability and monitoring systems to ensure trust and reliability across pipelinesnBuild and optimize data models in modern cloud data warehouses (e.g. Snowflake BigQuery Databricks)nUse tools like DBT to create modular testable and well-documented transformation layersnOrchestrate and manage workflows using tools such as Airflow Prefect or DagsternOptimize pipelines and queries for performance scalability and cost efficiencynContribute to the design of the data architecture supporting AI agents and autonomous workflowsnEnable self-service analytics and reporting for engineering and product teamsnCollaborate across teams to define and implement best practices for data engineering in an AI-first platform

3 years of hands-on experience in data engineering analytics engineering or a related role in a production environmentnProficiency in Python and SQL including pipeline development automation and performance optimizationnHands-on experience with cloud data warehouses (e.g. Snowflake BigQuery or Databricks)nExperience implementing monitoring logging and observability for data pipelinesnExperience with data modelingnB.S. in Computer Science or similar or equivalent industry experience

Experience building AI/LLM-powered data pipelines including RAG systems and integrations with APIs such as OpenAI or AnthropicnExperience with real-time/streaming data systems such as Apache Kafka Flink or Spark Structured StreamingnExperience with workflow orchestration tools such as Airflow Prefect or DagsternKnowledge of MLOps workflows including feature engineering model deployment and monitoring (e.g. MLflow Vertex AI)nExperience with data quality governance and lineage tools (e.g. Great Expectations Monte Carlo)nExperience building and maintaining ELT pipelines using DBTnExperience building dashboards and analytics using tools like Tableau Looker or Power BInWorking knowledge of cloud platforms (AWS GCP or Azure) and associated data services (e.g. S3 Glue Dataflow)