Data Engineering Manager — Video Engineering

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The Video Engineering group is looking for an Engineering Manager to lead a team that supports data collection software, firmware, and hardware test environments powering next-generation Apple products.

This role sits at the intersection of engineering, operations, and vendor management, and is ideal for someone who can lead a technical team, drive cross-functional execution, and manage the people and processes behind our test infrastructure and data pipelines.

Our team bridges engineering, test operations, and external partners to keep our data collection systems and test environments running smoothly and scaling with the needs of the business.

As an Engineering Manager on this team, you will oversee the day-to-day operations of our data collection software, firmware, and hardware test infrastructure, manage a team of engineers and technical staff, and coordinate with vendors and suppliers to source, onboard, and maintain the equipment and services our team relies on.

You'll work closely with engineering, safety/compliance, and business partners to plan and execute projects, review technical plans, and ensure our team has what it needs to deliver high-quality test data and results that support ML model and algorithm testing and validation.

This role requires a minimum of 5 days per week working on-site in the office.

BS and a minimum of 10 years relevant industry experience. 5+ years in an engineering/technical role and 5+ years in people management or team lead capacity.

Experience with internal data collection software, firmware, and hardware test environments, including working knowledge of test methodologies, automation, and hardware bring-up workflows sufficient to understand test setups, review technical plans, and ask informed questions.

Understanding of ML model/algorithm testing and validation, including how test data quality and collection methodology impact model evaluation, along with experience in data acquisition pipelines (sensor/instrumentation data collection, data quality/validation, and storage/pipeline infrastructure) and data management practices.

Ability to interpret and communicate data-driven insights to guide operational decisions and report to engineering and business stakeholders, and to translate technical requirements into plans, timelines, and deliverables for technical and non-technical audiences. Proficiency in prompt engineering and AI-assisted development workflows, with experience tackling complex debugging, architectural trade-offs, or automation tasks.

Experience managing engineering or technical teams within a hardware development, test/validation, or lab operations environment. Track record of building or scaling operational processes (e. g.

, test infrastructure, lab space, staffing models) to support a growing team. Experience managing cross-functional technical projects across engineering, operations, and external vendors, including vendor/supplier relationship management. Strong program management skills, with the ability to track multiple parallel workstreams and prioritize competing demands.

Excellent written and verbal communication skills, with the ability to bridge conversations between engineers, leadership, and business partners. Demonstrated people-leadership skills: mentoring, coaching, and developing engineers or technicians at varying experience levels, and fostering an inclusive, high-performing team culture.