Engineering Program Manager, Data Solutions & Initiatives

The people here at Apple dont just create products - they create the kind of wonder thats revolutionized entire industries. Its the diversity of those people and their ideas that inspires the innovation that runs through everything we do from amazing technology to industry-leading environmental efforts. Join Apple and help us leave the world better than we found it. We work in a startup atmosphere where individuals take ownership and have significant impact on the final product. nnWe are a team within Apples Worldwide Sales organization Data Solutions u0026 Initiatives (DSI) we are experts in product design engineering and portfolio management and seeking a highly technical execution-focused Engineering Program Manager to drive delivery of large-scale strategic business programs. This role is critical to translating product and technical strategy into executable plans while remaining deeply engaged in the technical realities of what is being ideal candidate brings a strong technical background and leverages that expertise dailyunderstanding architectures data flows development lifecycles and technical constraints at a system level. You are comfortable facilitating design and architecture discussions evaluating trade-offs and working hands-on with delivery teams to remove blockers. You excel at aligning cross-functional partners creating structure in ambiguous environments and ensuring high-quality delivery of complex programs that span multiple teams and domains.

In this role you will own the planning coordination and execution of complex engineering programs from concept through launch and post-launch stabilization. You will partner closely with engineering product design and other stakeholders to define scope outcomes technical roadmaps and delivery plans while driving execution across the full software development lifecycle. This role requires a blend of strategic thinking program management rigor and deep technical understanding. You will actively participate in requirements definition design and architecture reviews Agile ceremonies and delivery forums while ensuring teams remain aligned risks are proactively managed and outcomes meet both technical and business responsibilities will include:nn- Own end-to-end delivery of complex engineering programs from concept through launch and post-launch stabilization ensuring alignment with product technical and business objectives.n- Partner with our engineering product and design teams to define program scope roadmaps milestones timelines dependencies and success metrics.n- Drive execution rigor across the SDLC including planning tracking and measuring progress against key milestones deliverables and quality standards.n- Facilitate cross-team delivery and Agile execution leading forums such as Scrum of Scrums sprint planning sprint reviews and stand-ups to maintain momentum and alignment.n- Actively engage in technical discussions including requirements definition design and architecture reviews to understand system dependencies evaluate trade-offs and surface risks early.n- Identify assess and mitigate delivery risks and bottlenecks proactively removing roadblocks and driving resolution across teams.n- Influence technical and operational decisions by understanding architectures data flows infrastructure and (where applicable) ML workflows and their impacts.n- Contribute hands-on technical expertise when needed including analyzing designing debugging and modifying software or systems to unblock teams validate approaches or de-risk delivery.n- Apply working knowledge of modern programming languages and technologies to review prototype test and debug code as appropriate to support program execution and technical decision-making.n- Ensure functional validation and delivery quality confirming features meet business goals user needs and defined requirements in partnership with product and QA teams.n- Manage program resources and financials including capacity planning budget tracking and trade-off analysis.n- Communicate program health and outcomes through clear data-driven updates to technical teams leadership and stakeholders.n- Drive continuous improvement of delivery processes tooling and operating models to improve predictability quality and international travel may be required.

Program Management: Lead the end-to-end management of engineering programs ensuring projects are completed on time within scope and in accordance with product roadmaps. Drive program execution from initial planning to -Functional Collaboration: Work closely with engineers product managers and other stakeholders to define project/program scope milestones and timelines. Ensure effective communication across teams and ensure all parties are aligned on Scheduling u0026 Resource Allocation: Create and maintain detailed project plans timelines and resource allocation. Ensure that all resources are being used efficiently and that potential bottlenecks are identified and resolved Management: Identify potential risks and issues that may impact project deadlines scope or quality. Develop and implement mitigation plans to address these risks and ensure the program stays on Tracking: Monitor and report on key project metrics and deliverables. Provide regular updates to leadership on progress potential risks and opportunities for improvementnProcess Improvement: Continuously evaluate and improve internal processes to enhance team efficiency reduce time-to-market and improve overall program Communication: Serve as the primary point of contact for internal and external stakeholders ensuring all parties are informed of project status changes and Proficiency: Analyze business requirements (including data analysis) and translate them into actionable technical Validation: Ensure the feature/s developed by engineering team meet the intended business goals and user needs. This includes confirming that the feature fulfills the customer or user stories as expected. Work with product managers to ensure that the feature behaves in a way that is intuitive for end users and solves the problem it was designed to Assurance and Continuous Improvement: Ensure the delivery of high-quality products/features by working with engineering and QA teams to establish testing protocols and quality -Launch Monitoring and Feedback: Ensure post-launch monitoring and performance evaluations are in place to track the success of the project after its deployed. Work with engineering and product teams to address any post-launch issues and gather feedback for future iterations.

7 years of experience in engineering program management or equivalent technical delivery degree in Engineering Computer Science or equivalent practical experience owning end-to-end delivery of complex engineering programs across the full hands-on technical background with the ability to understand and engage in system architecture data flows APIs and development SQL Python or visualization tool experience (e.g. Tableau) to write basic queries/scripts supporting analysis QA validation debugging and engineering experience leading cross-functional engineering efforts across software platform data infrastructure and quality to actively engage in technical problem-solving including reviewing designs debugging issues and contributing code or prototypes when needed to unblock experience with Agile delivery and program management tools (e.g. Jira) and execution organizational skills with the ability to manage ambiguity dependencies and competing priorities in fast-paced written and verbal communication skills with the ability to clearly communicate technical and program status to diverse with capacity planning milestone tracking and delivery risk to travel internationally if needed.

PMP or equivalent program management supporting AI/ML-driven products including familiarity with ML development lifecycles data pipelines and model deployment -on experience with modern data platforms (e.g. Snowflake Trino Dremio).nExperience with large-scale platform/infrastructure in high-performance or product-led organizations where delivery speed quality and scale are critical. nStrong analytical mindset with the ability to use data to inform trade-offs prioritization and execution decisions.