Software Engineer, Data Solutions ASE

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

• Fertility benefits: Not verified
• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

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Relocation assistance

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Childcare support

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Learning budget

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Verification

Not verified last checked Jun 13, 2026

Salary

Not verified not verified - source not recorded; timestamp not recorded

401(k) match

Listed Source: EMPLR_CONTRIB_INCOME_AMT. source Last checked Jun 13, 2026.

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Market context

Median wage (BLS OEWS)

$111,944 national median

Projected growth (BLS Employment Projections)

+13.7% - Much faster than average

87% above the BLS national median for data and ml aggregate.

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Schedule

Shift type

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Weekend work

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Application

Cover letter

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Assessment

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Deadline

Not stated

Where they hire

State eligibility is not yet verified.

About this role

Software Engineer, Data Solutions ASE New York City, United States of America Imagine what you could do here. At Apple, new ideas become great products, services, and customer experiences quickly. Bring focus, rigor, and curiosity to your work and help shape the future of Apple's data infrastructure. Apple is seeking an experienced software engineer to join the Data Solutions team within Data Services, responsible for building and evolving the distributed data systems that power Apple's most critical consumer services - including Apple Music, TV, and Podcasts. You'll work on high-scale streaming and data processing platforms, solving hard problems around cross-datacenter replication and getting user data to the edge as fast as possible. Your work will directly impact hundreds of millions of Apple users and the teams that build experiences for them. Apple's Data Solutions team, within the broader ASE Data Services organization, builds and operates data infrastructure that is reliable, scalable, and low-latency. The team focuses on real-time data streaming, large-scale data processing, and optimizing cross-datacenter replication to bring user data to the edge with the smallest possible latency. Apache Kafka plays a central role in our streaming and replication infrastructure, and familiarity with its ecosystem is a meaningful advantage. Our systems sit at the heart of services like Apple Music, TV, and Podcasts, ensuring that data is available where and when it's needed - anywhere in the world. A key focus for this team is automating existing systems and integrating them into a centralized cloud platform - modernizing the

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