Data Engineer Jobs at Apple with Visa Sponsorship
Data Engineer jobs at Apple sit at the intersection of massive-scale infrastructure and consumer product development, covering data pipelines, analytics engineering, and platform work across hardware and services. Apple has a strong track record of sponsoring international talent for this function across multiple visa categories.
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INTRODUCTION
Apple is where individual imaginations gather together, committing to the values that lead to great work. Every new product we build, service we create, or Apple Store experience we deliver is the result of us making each other's ideas stronger. That happens because every one of us shares a belief that we can make something wonderful and share it with the world, changing lives for the better. It's the diversity of our people and their thinking that inspires the innovation that runs through everything we do. When we bring everybody in, we can do the best work of our lives. Here, you'll do more than join something - you'll add something.
DESCRIPTION
We are seeking a highly experienced and strategic Machine Learning Data Engineer to drive our machine learning data with a strong focus on quality. In this role, you will transform ambiguous data challenges into scalable processes, clear policies, and high-fidelity datasets that power diverse ML use cases, specifically focused on innovative consumer products and user-facing technologies.
You will act as the crucial link between technical tools and infrastructure, cross-functional engineering teams, and regulatory compliance (including privacy, legal, and consumer data protection). If your passion is making sense of complex data, designing data evaluation frameworks, and leading initiatives to maximize model ROI through rigorous data quality, we want you on our team.
Responsibilities
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Drive ML Data Quality & Validation: Lead the continuous quality management of ML datasets, with a specific focus on human-generated data. Design and execute rigorous dataset validation processes, incorporating real-time feedback loops to immediately identify, flag, and resolve quality issues before they impact model performance.
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Translate Policy to Scalable Processes: Develop sophisticated data processes and policies for complex consumer product domains driven by innovative technology. Convert ambiguous data quality problems and legal/regulatory constraints into precise, scalable workflows and data guidelines for user-facing features and edge cases.
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Build Data Evals & Metrics: Design and implement robust data evaluation frameworks. Identify key data-centric drivers of model performance and define the metrics that rigorously track data quality, consistency, and integrity at the granular level.
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Ensure Privacy, Legal, & Regulatory Compliance: Act as a steward of data integrity. Integrate privacy requirements, legal data quality standards, and consumer protection regulations directly into the data workflows and policies.
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Cross-Functional Leadership: Serve as a bridge between technical and non-technical audiences. Produce compelling analytical write-ups, dashboards, and data visualizations to convey insights, advocate for data strategy, and align engineering stakeholders.
MINIMUM QUALIFICATIONS
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BS in Computer Science, Data Engineering, Data Science, Mathematics, or a related field; or equivalent industry experience.
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Experience in data analysis, data engineering, and machine learning data operations.
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Experience designing data quality control processes, data curation workflows, or Human-in-the-Loop initiatives.
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Experience managing or coordinating cross-functional projects spanning multiple technical teams or organizations, leading end-to-end data strategy for ML development lifecycle, including iterating rapidly to drive improvements.
PREFERRED QUALIFICATIONS
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10+ years of experience in data analysis or ML data operations, including identifying trends, generating summary statistics, and drawing insights from quantitative and qualitative data.
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Experience operating within global data privacy frameworks (e.g., GDPR, CCPA) and aligning consumer ML data handling with legal compliance and ethical guidelines.
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Proven background in leading complex, cross-functional programs focused specifically on ML data quality at scale.
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Experience with prompt engineering, machine learning tools, and fine-tuning Large Language Models (LLMs).
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Demonstrated ability to consult with diverse engineering stakeholders to gather requirements, explain complex models, and iterate rapidly to drive improvements.
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Excellent written and verbal communication skills, with a specialized ability to distill highly technical analyses to non-technical audiences effectively.
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Exceptional problem-solving skills, adaptability, and agility to navigate high ambiguity, learn proprietary tools quickly, and thrive in a fast-paced environment.
PAY & BENEFITS
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $181,100 and $318,400, and your base pay will depend on your skills, qualifications, experience, and location.
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation.
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
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Get Access To All JobsTips for Finding Data Engineer Jobs at Apple
Align your portfolio to Apple's data stack
Apple's Data Engineer roles consistently require experience with large-scale distributed systems and tools like Spark, Presto, and internal pipeline orchestration. Build or document projects that demonstrate you've worked with data at consumer-product scale, not just enterprise BI tooling.
Target postings that name your visa type
Apple's Data Engineer job descriptions often specify which work authorization types they'll support. Filter for roles that explicitly list your visa category, whether H-1B, E-3, or TN, so you're not eliminated at the recruiter screening stage before a conversation starts.
Understand Apple's legal team handles PERM internally
Apple manages Green Card sponsorship through PERM labor certification with its in-house immigration team. Knowing this means you can ask directly during offer negotiation whether the role is designated for employer-sponsored permanent residency, and at what seniority level that typically begins.
Use Migrate Mate to surface Apple's open roles
Apple posts Data Engineer openings across teams with varying sponsorship scopes. Use Migrate Mate to filter specifically for Apple roles that match your visa type, so you're spending time only on positions where sponsorship is already confirmed.
Request premium processing before your start date
If you're transferring an existing H-1B to Apple, USCIS premium processing gets a decision within 15 business days. Coordinate with Apple's immigration team early so the I-129 petition is filed with enough runway before your intended first day.
Validate your OPT STEM extension eligibility before accepting
Apple is an E-Verify participant, which is a requirement for F-1 students on STEM OPT extensions. Before signing an offer, confirm your degree field appears on the official STEM Designated Degree Program List so your 24-month extension remains valid from day one.
Frequently Asked Questions
Does Apple sponsor H-1B visas for Data Engineers?
Yes, Apple sponsors H-1B visas for Data Engineers and has done so consistently across teams in areas like machine learning infrastructure, analytics, and platform engineering. Sponsorship decisions are role-specific and handled by Apple's in-house immigration team. Because the H-1B is subject to an annual lottery, timing your application cycle and having your offer in place before the March registration window matters.
How do I apply for Data Engineer jobs at Apple?
Applications go through Apple's careers portal at jobs.apple.com. Search for Data Engineer roles and filter by location, typically Santa Clara Valley or Seattle. Tailoring your resume to highlight pipeline architecture, data modeling, and distributed systems experience improves your chances at the recruiter screen. You can also browse Apple's open Data Engineer roles filtered by visa type on Migrate Mate before applying directly.
Which visa types does Apple commonly sponsor for Data Engineer roles?
Apple sponsors H-1B, H-1B1 visa (for Chilean and Singaporean nationals), E-3 visa (for Australian nationals), and TN visas for qualifying Canadian and Mexican candidates. F-1 OPT and STEM OPT extensions are also supported for recent graduates. For longer-term pathways, Apple sponsors EB-2 and EB-3 Green Cards through the PERM labor certification process for eligible employees.
What qualifications does Apple expect for Data Engineer roles?
Apple's Data Engineer postings typically expect a bachelor's or master's degree in computer science, engineering, or a related technical field. Hands-on experience with distributed data processing frameworks like Spark or Flink, proficiency in SQL and Python, and familiarity with cloud infrastructure are standard requirements. Senior roles add expectations around data platform design and cross-functional stakeholder work with product and machine learning teams.
How do I navigate the timeline from offer to visa filing at Apple?
Once you have a signed offer, Apple's immigration team initiates the appropriate petition based on your visa category. For H-1B cap-subject cases, this process is tied to the annual USCIS registration window in March, with an October 1 start date at the earliest. For cap-exempt transfers or E-3 and TN filings, processing can move faster. Expect several weeks of internal preparation before any government filing begins.