Engineering Program Manager, US Decision Intelligence

Socket.dev; Cupertino (CA); On-site; USD 190,000 - 230,000; Full time

Job summary

Apple's US Decision Intelligence team in Cupertino seeks an Engineering Program Manager to scale AI-enabled insights generation and data operations across data engineering, data science, and business teams. You will coordinate cross-functional work to ensure insights are accurate, actionable, and embedded in sales workflows.

The role demands strong execution, communication, and program management, with the ability to navigate ambiguity, manage multiple workstreams, and partner with engineering,

Qualifications

• Experience translating business needs into actionable execution plans.
• Proven track record leading cross-functional data/Analytics programs from planning to delivery.
• Strong data operations knowledge including data quality checks and governance.
• Excellent communication and stakeholder management across technical and non-technical audiences.
• Experience with AI/GenAI insights workflows is a plus.

Responsibilities

• Own the execution plan for insights generation and data operations workstreams, ensuring priorities, timelines, owners, dependencies, and risks are clearly managed.
• Coordinate the end-to-end delivery cycle for insights, from business requirement gathering to data readiness, QA, stakeholder review, publishing, and post-launch monitoring.
• Help establish repeatable operating processes for how insights are requested, built, validated, released, monitored, and improved over time.
• Track and unblock dependencies across data sources, pipelines, semantic layers, AI-generated outputs, and downstream business workflows.
• Support launch readiness by making sure data quality, business logic, access, documentation, support plans, and stakeholder communications are in place.
• Communicate status, risks, tradeoffs, and decisions clearly to engineering leads, business partners, and senior leadership.

Skills

Cross-functional collaboration

Program management

Data operations

AI/GenAI knowledge

Stakeholder communication

Risk management

Education

BS degree in Engineering/CS/Data Science

Tools

Wrike

Confluence

Tableau

GitHub

Airflow

dbt

Snowflake

Job description

Imagine what you could do here. At Apple, new ideas have a way of becoming outstanding products, services, and customer experiences very quickly. Bring passion and dedication to your job, and there's no telling what you could accomplish. Apple’s Sales organization generates the revenue needed to fuel our ongoing development of products and services. This, in turn, enriches the lives of hundreds of millions of people around the world. We are, in many ways, the face of Apple to our largest customers. Apple's US Decision Intelligence (DI) team is looking for a talented individual who is passionate about crafting, implementing, and operating AI solutions that have a direct and measurable impact on Apple Sales and its customers. We’re looking for an Engineering Program Manager with strong execution, communication, and technical program management skills to help scale AI-enabled insights generation and data operations. You’ll be responsible for coordinating cross-functional work across data engineering, data science, and business teams to ensure insights are accurate, actionable, operationally reliable, and embedded into real-world sales workflows.

Description

In this role, you will:

• Own the execution plan for insights generation and data operations workstreams, ensuring priorities, timelines, owners, dependencies, and risks are clearly managed.
• Coordinate the end-to-end delivery cycle for insights, from business requirement gathering to data readiness, QA, stakeholder review, publishing, and post-launch monitoring.
• Help establish repeatable operating processes for how insights are requested, built, validated, released, monitored, and improved over time.
• Track and unblock dependencies across data sources, pipelines, semantic layers, AI-generated outputs, and downstream business workflows.
• Support launch readiness by making sure data quality, business logic, access, documentation, support plans, and stakeholder communications are in place.
• Communicate status, risks, tradeoffs, and decisions clearly to engineering leads, business partners, and senior leadership.

We’re looking for someone with an eagerness and ability to learn new skills and solve dynamic problems in an encouraging and expansive environment.

Experience driving cross-functional data or analytics programs from planning through execution, including roadmap tracking, milestone management, dependency coordination, risk management, and stakeholder communication.

Strong understanding of data operations workflows, including data ingestion, data quality checks, business logic validation, reporting cycles, issue triage, and operational support.

Ability to partner with engineering, data science, analytics, product, business operations, and sales operations teams to translate business needs into clear execution plans.

Strong ability to manage ambiguity, clarify scope, document decisions, align owners, and drive execution across multiple teams and priorities.

Experience with AI-enabled analytics or insights workflows, including LLM-generated summaries, automated insights, data narratives, quality review, and human-in-the-loop validation.

Strong attention to detail and ability to identify risks related to data quality, logic gaps, unclear ownership, missed dependencies, stakeholder alignment, or delivery readiness.

Strong communication skills, with the ability to explain data, process, and technical topics clearly to both technical and non-technical audiences.

Ability to work in a fast-paced, dynamic, constantly evolving business environment.

Ability to manage multiple workstreams in a fast-paced environment while balancing planned roadmap work, operational issues, and ad hoc business requests.

B.S. degree in Engineering, Computer Science, Data Science, Information Systems, or a related field, or equivalent practical experience.

Preferred Qualifications

Familiarity with modern AI/GenAI capabilities for insights generation, including automated summaries, natural-language explanations, anomaly detection, recommendations, and agentic workflows.

Experience working with tools such as Wrike, Confluence, Tableau, GitHub, Airflow, dbt, Snowflake, Spark, Databricks, or similar data and engineering platforms.

Ability to partner with engineering teams on technical readiness across data pipelines, APIs, model integrations, monitoring, data refreshes, access controls, and launch criteria.

Understanding of operational risks in data and AI products, including stale data, broken pipelines, metric inconsistencies, model behavior issues, permission gaps, and unclear ownership.

Experience working with globally distributed engineering or data teams and coordinating execution across multiple time zones.

Strong judgment on when to elevate technical risks, adjust scope, pause delivery, or align leadership on tradeoffs.

Advanced Degree (MS or Ph.D.) in Computer Science, Engineering, Data Science, Information Systems, Statistics, Business Analytics, Operations Research, or a related quantitative/technical field is preferred.