Software Development Engineer - Data

Description

The ASE Content Data Engineering team is responsible for the internal business intelligence infrastructure that powers Apple's online media store. The data models and reports developed by this team supply information to engineering, business operations, and external content providers regarding the status of online media, including workflow status, availability, and incoming and outgoing volume.

This engineer will own and evolve a large portfolio of data pipelines and reporting systems, driving the ongoing migration from legacy infrastructure to modern pipeline orchestration and cloud-based storage, while also delivering net-new reports and data models in response to business, engineering, and regulatory needs. The role demands a blend of engineering rigor, data fluency, and a strong reliability mindset: the team's reports directly support legal and compliance obligations with hard, externally-imposed deadlines.

The ideal candidate brings a bias toward automation and self-healing pipelines over manual intervention, and is comfortable managing a broad portfolio of concurrent work, balancing urgent pipeline fixes against longer-horizon migration and enhancement projects. They can independently troubleshoot and resolve ambiguous, production-impacting issues under time pressure, and communicate technical findings clearly to non-engineering stakeholders across legal, business operations, and content provider teams. Knowledge of or genuine curiosity about online media is a plus.

Responsibilities:

Design, build, and maintain automated data pipelines and reporting systems across a hybrid stack spanning Oracle, Spark, Hadoop, and cloud object storage

Drive the migration of legacy report jobs to modern pipeline orchestration and cloud infrastructure, ensuring reliability, observability, and maintainability

Investigate and resolve pipeline failures, performance bottlenecks, and data quality issues across a large, interdependent reporting estate covering all content domains

Develop and maintain legal and regulatory-compliance reports where accuracy, auditability, and on-time delivery are non-negotiable

Onboard and publish curated datasets from operational data stores to the Apple Data Lakehouse, ensuring proper data governance, lineage documentation, and PII tagging

Extend and enhance internal content data platform models across all content domains: propagating schema changes, adding new columns and descriptors, and maintaining the accuracy of the platform's content-intelligence surface

Execute controlled, legally-gated production data modifications and archival/deletion programs under change control and with required legal approval

Contribute to the evolution of AI-assisted data tooling (e.g., Text-to-SQL), automating and accelerating how stakeholders access and query content data

Preferred Qualifications

Familiarity with Iceberg / Parquet-based table formats

Proficiency in macOS and Linux server environments

Experience using GenAI tools (e.g., Claude, OpenAI tools) to accelerate engineering tasks

Familiarity with cloud object storage migration patterns (HDFS to S3)

Experience with EKS or other cloud-based compute platforms

Familiarity with Trino or other distributed SQL query engines

Experience with Flink or Flink SQL for stream-based data processing

Familiarity with GenAI-assisted data access patterns (e.g., MCP servers, Text-to-SQL, LLM-assisted data documentation)

Familiarity with Tableau or similar data visualization and dashboarding tools

Experience with shell scripting for automation and pipeline support

Experience with Java development

Minimum Qualifications

Minimum 1 year of experience as a Software Engineer, Data Engineer, or equivalent role

Strong experience with Spark and Spark SQL, including performance tuning and resource optimization

Strong experience with Hadoop, HDFS, and/or S3-compatible object storage

Hands-on experience with Python scripting for data processing and automation

Experience writing SQL and PL/SQL on Oracle, including query optimization

Experience building and maintaining automated data pipelines and job scheduling systems (e.g. Airflow)

Experience with CI/CD workflows and version-controlled deployment of data pipeline code

Hands-on experience with Kubernetes for container-based workload execution

Bachelor's degree in Computer Science, Software Engineering, Data Science, or a related technical field OR Hands-on engineering experience and a demonstrable track record of building and maintaining production data systems are weighted equally alongside formal academic credentials.

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 $225,300, 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.

Client-provided location(s): Cupertino, CA

Job ID: apple-200673748-0836

Employment Type: OTHER

Posted: 2026-08-01T00:33:01