Senior Data Engineer, Platform Financial Governance, Apple Data Platform

The Apple Data Platform powers analytics, machine learning, and critical decision-making systems across Apple. As the scale of our data and compute grows, cost efficiency and fiscal stewardship are vital to maintaining Apple's culture of innovation and responsibility.

Description

We are seeking a Senior Data Engineer for the Platform Financial Governance team to help build the technical foundation of Apple's infrastructure economy. In this role, you will design and implement the scalable data systems that make "cost" a first-class citizen in our engineering stack. You will play a key role in building a robust financial governance platform developing the data models, real-time pipelines, and enforcement mechanisms that ensure every unit of compute is accounted for and optimized. You will work closely with Service engineers and cross-functional partners to build tooling that allows engineering teams to self-govern their usage while providing leadership with granular visibility into total cost of ownership (TCO).","responsibilities":"Design & Build Financial Pipelines: Develop and maintain petabyte-scale data pipelines that ingest, normalize, and attribute usage telemetry (Compute, GPU, Storage, Network) from hybrid cloud environments.

Implement Governance Logic: Write the code and rules engines for financial governance, including automated budget tracking, quota management systems, and anomaly detection alerts.

Data Quality & Reliability: Own the health of financial datasets. Implement rigorous data quality checks (SLAs), lineage tracking, and auditing mechanisms to ensure reporting accuracy.

FinOps Tooling: Build and expose APIs that deliver cost metrics to downstream engineering tools (e.g., CI/CD pipelines, chargeback dashboards, and resource tagging bots).

System Optimization: Continuously tune and optimize data processing jobs (Spark/Flink) and storage layouts (Iceberg/Delta) to ensure the governance platform remains performant and cost-effective.

Collaboration: Partner with Data Scientists and Platform Engineers to integrate economic models into production systems and ensure seamless data flow across the platform.

Preferred Qualifications

Cloud Cost Familiarity: Experience working with cloud billing data (AWS Cost Explorer, CUR files) or general cost management principles.

Container Orchestration: Experience working with Kubernetes concepts (pods, namespaces, resource requests/limits).

Streaming Data: Experience building real-time data pipelines using Kafka, Flink, or Spark Streaming.

Minimum Qualifications

Experience: 5+ years of experience in Data Engineering, Platform Engineering, or Backend Software Engineering.

Big Data Proficiency: Strong proficiency in distributed data processing frameworks (e.g., Apache Spark, Flink, Trino/Presto) and modern table formats (Iceberg, Delta Lake).

Coding Expertise: Strong, production-grade coding skills in Java, Scala, or Python, with a solid grasp of data structures, algorithms, and software design patterns.