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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Get Access To All JobsAt Apple, we build products and services that enrich people’s lives. Apple Ads helps customers discover relevant products and content while enabling developers, publishers, and advertisers to grow their businesses. Privacy is fundamental to how we design and build our advertising platform. The Apple Ads engineering organization operates large-scale data systems that process and transform high-volume advertising events into reliable datasets and products used for reporting, measurement, analytics, and other critical business functions. We are looking for a Software Engineer with strong software engineering fundamentals and experience building large-scale distributed data processing systems. In this role, you will design, develop, and operate production data pipelines using technologies such as Apache Spark, Kafka, Java/Scala, cloud storage, and modern data lake technologies. You will work on challenging problems involving large-scale batch and streaming data processing, data correctness, privacy, reliability, scalability, and performance. You will have opportunities to own systems end-to-end—from architecture and implementation through deployment, observability, and production support.
Description
As a Software Engineer on the Apple Ads data engineering team, you will help build the next generation of scalable data processing and reporting infrastructure. You will design and implement distributed data pipelines that process large volumes of advertising events across batch, near-real-time, and streaming execution environments. You will work on systems where correctness, data quality, performance, reliability, and privacy are critical. The ideal candidate is a strong software engineer who also has hands-on experience with Apache Spark and large-scale data processing. You should be comfortable reasoning about distributed systems, debugging complex data pipelines, optimizing Spark workloads, designing data models, and building production-quality software around big-data processing frameworks. You will collaborate with engineers, product teams, data scientists, SREs, and other cross-functional partners to translate business and technical requirements into scalable data solutions.
Responsibilities
- Design, develop, and operate large-scale distributed data processing pipelines using Apache Spark and related big-data technologies.
- Build reliable batch, near-real-time, and streaming pipelines for processing high-volume advertising and measurement data.
- Develop production-quality software primarily using Java, Scala, and/or Python.
- Design scalable data architectures for processing and storing very large datasets.
- Build pipelines using technologies such as Spark, Kafka, S3/object storage, Apache Iceberg, Hadoop, and cloud-native infrastructure.
- Develop efficient data transformations, aggregations, joins, and data-processing algorithms over large datasets.
- Analyze and optimize Spark applications for performance, memory utilization, shuffle efficiency, parallelism, and compute cost.
- Design systems that gracefully handle late-arriving data, retries, partial failures, reprocessing, and evolving data schemas.
- Build strong data-quality controls, validation mechanisms, reconciliation frameworks, and monitoring to ensure correctness throughout the data lifecycle.
- Design systems with privacy, security, and appropriate data-handling principles built into the architecture.
- Develop observability, metrics, alerting, and debugging capabilities for production data pipelines.
- Investigate and resolve complex issues across distributed compute, storage, orchestration, and downstream data systems.
- Participate in architecture and design reviews and contribute to technical decisions for evolving the data platform.
- Write clean, maintainable, well-tested code and participate actively in code reviews.
- Own services and pipelines through their complete lifecycle, including design, development, deployment, monitoring, and production support.
- Collaborate with cross-functional engineering and product teams to deliver scalable solutions for Apple Ads.
Preferred Qualifications
- Experience designing and operating petabyte-scale data processing systems.
- Deep expertise in Apache Spark performance tuning and optimization.
- Experience with Apache Iceberg or similar modern data lake/lakehouse technologies.
- Experience with both batch and real-time/streaming architectures, including Kafka and/or Flink.
- Experience building data platforms or processing frameworks that are reused by multiple teams or pipelines.
- Experience with AWS technologies, including S3 and Kubernetes/EKS or equivalent cloud platforms.
- Experience running distributed workloads using Kubernetes and containerized environments.
- Familiarity with analytical data stores and query engines such as Druid, Trino, or similar technologies.
- Experience designing systems that support replay, backfills, reprocessing, and late-arriving data.
- Experience implementing data-quality, reconciliation, lineage, or data-contract frameworks.
- Understanding of privacy-preserving data processing and secure handling of large-scale datasets.
- Experience building systems for advertising, measurement, reporting, or analytics.
- Demonstrated ability to take ownership of complex projects and drive them from design through production.
Minimum Qualifications
- 3+ years of professional software engineering or data engineering experience building production systems.
- Strong computer science fundamentals, including data structures, algorithms, concurrency, and distributed systems concepts.
- Strong programming skills in Java and/or Scala, with experience writing production-quality software.
- Hands-on experience building and operating large-scale data pipelines using Apache Spark.
- Strong understanding of Spark concepts including partitioning, shuffles, joins, caching, execution plans, memory management, and performance tuning.
- Experience designing distributed batch and/or streaming data processing systems.
- Experience with technologies such as Kafka, Hadoop, S3/object storage, or equivalent large-scale data infrastructure.
- Strong SQL skills and experience working with large analytical datasets.
- Expertise in distributed systems and data processing technologies (e.g. Spark, Kafka, Flink).
- Understanding of data modeling, partitioning strategies, schema evolution, and efficient storage formats such as Parquet.
- Experience building reliable production systems with appropriate testing, monitoring, alerting, and operational support.
- Strong debugging and problem-solving skills, particularly across complex distributed systems.
- Ability to communicate effectively and collaborate with technical and non-technical cross-functional partners.
- Bachelor’s degree in Computer Science, Software Engineering, Computer Engineering, or a related technical field, or equivalent practical experience.
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 $150,400 and $277,600, 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. Learn more about Apple Benefits
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
At Apple, we build products and services that enrich people’s lives. Apple Ads helps customers discover relevant products and content while enabling developers, publishers, and advertisers to grow their businesses. Privacy is fundamental to how we design and build our advertising platform. The Apple Ads engineering organization operates large-scale data systems that process and transform high-volume advertising events into reliable datasets and products used for reporting, measurement, analytics, and other critical business functions. We are looking for a Software Engineer with strong software engineering fundamentals and experience building large-scale distributed data processing systems. In this role, you will design, develop, and operate production data pipelines using technologies such as Apache Spark, Kafka, Java/Scala, cloud storage, and modern data lake technologies. You will work on challenging problems involving large-scale batch and streaming data processing, data correctness, privacy, reliability, scalability, and performance. You will have opportunities to own systems end-to-end—from architecture and implementation through deployment, observability, and production support.
Description
As a Software Engineer on the Apple Ads data engineering team, you will help build the next generation of scalable data processing and reporting infrastructure. You will design and implement distributed data pipelines that process large volumes of advertising events across batch, near-real-time, and streaming execution environments. You will work on systems where correctness, data quality, performance, reliability, and privacy are critical. The ideal candidate is a strong software engineer who also has hands-on experience with Apache Spark and large-scale data processing. You should be comfortable reasoning about distributed systems, debugging complex data pipelines, optimizing Spark workloads, designing data models, and building production-quality software around big-data processing frameworks. You will collaborate with engineers, product teams, data scientists, SREs, and other cross-functional partners to translate business and technical requirements into scalable data solutions.
Responsibilities
- Design, develop, and operate large-scale distributed data processing pipelines using Apache Spark and related big-data technologies.
- Build reliable batch, near-real-time, and streaming pipelines for processing high-volume advertising and measurement data.
- Develop production-quality software primarily using Java, Scala, and/or Python.
- Design scalable data architectures for processing and storing very large datasets.
- Build pipelines using technologies such as Spark, Kafka, S3/object storage, Apache Iceberg, Hadoop, and cloud-native infrastructure.
- Develop efficient data transformations, aggregations, joins, and data-processing algorithms over large datasets.
- Analyze and optimize Spark applications for performance, memory utilization, shuffle efficiency, parallelism, and compute cost.
- Design systems that gracefully handle late-arriving data, retries, partial failures, reprocessing, and evolving data schemas.
- Build strong data-quality controls, validation mechanisms, reconciliation frameworks, and monitoring to ensure correctness throughout the data lifecycle.
- Design systems with privacy, security, and appropriate data-handling principles built into the architecture.
- Develop observability, metrics, alerting, and debugging capabilities for production data pipelines.
- Investigate and resolve complex issues across distributed compute, storage, orchestration, and downstream data systems.
- Participate in architecture and design reviews and contribute to technical decisions for evolving the data platform.
- Write clean, maintainable, well-tested code and participate actively in code reviews.
- Own services and pipelines through their complete lifecycle, including design, development, deployment, monitoring, and production support.
- Collaborate with cross-functional engineering and product teams to deliver scalable solutions for Apple Ads.
Preferred Qualifications
- Experience designing and operating petabyte-scale data processing systems.
- Deep expertise in Apache Spark performance tuning and optimization.
- Experience with Apache Iceberg or similar modern data lake/lakehouse technologies.
- Experience with both batch and real-time/streaming architectures, including Kafka and/or Flink.
- Experience building data platforms or processing frameworks that are reused by multiple teams or pipelines.
- Experience with AWS technologies, including S3 and Kubernetes/EKS or equivalent cloud platforms.
- Experience running distributed workloads using Kubernetes and containerized environments.
- Familiarity with analytical data stores and query engines such as Druid, Trino, or similar technologies.
- Experience designing systems that support replay, backfills, reprocessing, and late-arriving data.
- Experience implementing data-quality, reconciliation, lineage, or data-contract frameworks.
- Understanding of privacy-preserving data processing and secure handling of large-scale datasets.
- Experience building systems for advertising, measurement, reporting, or analytics.
- Demonstrated ability to take ownership of complex projects and drive them from design through production.
Minimum Qualifications
- 3+ years of professional software engineering or data engineering experience building production systems.
- Strong computer science fundamentals, including data structures, algorithms, concurrency, and distributed systems concepts.
- Strong programming skills in Java and/or Scala, with experience writing production-quality software.
- Hands-on experience building and operating large-scale data pipelines using Apache Spark.
- Strong understanding of Spark concepts including partitioning, shuffles, joins, caching, execution plans, memory management, and performance tuning.
- Experience designing distributed batch and/or streaming data processing systems.
- Experience with technologies such as Kafka, Hadoop, S3/object storage, or equivalent large-scale data infrastructure.
- Strong SQL skills and experience working with large analytical datasets.
- Expertise in distributed systems and data processing technologies (e.g. Spark, Kafka, Flink).
- Understanding of data modeling, partitioning strategies, schema evolution, and efficient storage formats such as Parquet.
- Experience building reliable production systems with appropriate testing, monitoring, alerting, and operational support.
- Strong debugging and problem-solving skills, particularly across complex distributed systems.
- Ability to communicate effectively and collaborate with technical and non-technical cross-functional partners.
- Bachelor’s degree in Computer Science, Software Engineering, Computer Engineering, or a related technical field, or equivalent practical experience.
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 $150,400 and $277,600, 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. Learn more about Apple Benefits
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
See all 122+ Data Engineer Jobs at Apple
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Data Engineer Jobs at Apple.
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.