Engineering PM: Data Analytics & Billing Pipelines

Apple Inc.; Seattle (WA); On-site; USD 167,000 - 296,000; Full time

Benefits offered by this job

Medical and dental coverage

Employee stock purchase plan

Relocation assistance

Job summary

Apple Services Engineering in Seattle, WA seeks an Engineering Program Manager for Analytics Data Engineering to drive data pipelines supporting Subscriptions and Billing across Apple Services. You will partner with small, agile data teams to deliver scalable datasets and analytics outcomes while upholding Apple's privacy standards.

You will manage scope, timelines and cross-functional plans, coordinating with Engineering, Analytics, Security, and Privacy to ship end-to-end data solutions in a

Qualifications

• 6+ years of PM experience in large-scale data engineering or analytics.
• Strong familiarity with Agile methodologies and cross-functional programs.
• Experience coordinating data pipelines and data products across teams.

Responsibilities

• Project manage and partner with other EPMs to coordinate data pipelines.
• Track multiple concurrent projects across scope, timelines, roadmaps, and resources.
• Collaborate with Engineering, Analytics, Security, Privacy, and QA to deliver data products.

Skills

Project management

Agile methodologies

Cross-functional collaboration

Communication skills

Privacy/compliance awareness

Education

BS in Information Systems, Data Science, Computer Science, Business, or Engineering

Tools

Big data technologies

Data pipelines

Data engineering concepts

Job description

Apple Services Engineering in Seattle, WA seeks an Engineering Program Manager for Analytics Data Engineering to drive data pipelines supporting Subscriptions and Billing across Apple Services. You will partner with small, agile data teams to deliver scalable datasets and analytics outcomes while upholding Apple's privacy standards.

You will manage scope, timelines and cross-functional plans, coordinating with Engineering, Analytics, Security, and Privacy to ship end-to-end data solutions in a