Americas Business Process Re-Engineering Data Engineer
Apple - Austin, United States of America
Posted Apr 15, 2026
Benefits
- Parental leave
- Not verified
- Non-birth-parent leave
- Not verified
- Family-building benefits
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- Fertility benefits: Not verified
- Adoption assistance: Not verified
- Surrogacy assistance: Not verified
- Mental health support
- Not verified
- Relocation assistance
- Not verified
- Childcare support
- Not verified
- Learning budget
- Not verified
- Verification
- Not verified last checked Jun 13, 2026
- Salary
- Not verified
- 401(k) match
- Listed Source: EMPLR_CONTRIB_INCOME_AMT. source Last checked Jun 13, 2026.
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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
Americas Business Process Re-Engineering Data Engineer Austin, United States of America Apple is where extraordinary people do their best work. If making a real impact excites you, a career here might be your dream - just be prepared to dream big. Apple's growing supply chain complexity demands innovative approaches beyond traditional data engineering. You'll join a team designing and building modern, scalable data infrastructure that powers analytics, machine learning, and AI-driven decision-making across Operations. You're passionate about building reliable data systems, staying ahead of technology trends, and thrive navigating ambiguity in a fast-paced environment. If this sounds like you, we'd love to talk. Engage with business and analytics teams to deeply understand data needs and translate requirements into robust, scalable engineering solutions that directly impact Operations decisions Design and implement end-to-end data pipelines and architectures from ingestion and transformation to delivery across batch and real-time streaming workloads Build and maintain high-quality data models (dimensional, relational, or knowledge graph-based) using modern transformation frameworks such as dbt, powering analytics and AIML use cases at scale Architect and operate data workflows using orchestration tools (e.g., Apache Airflow, etc) with built-in monitoring, alerting, and SLA management Implement data observability, lineage tracking, and validation frameworks to uphold data integrity and trustworthiness across the platform Collaborate with Data Scientists, ML Engineers, Software Engineers and Analysts to operationalize models and ensure data infrastructure supports production AIML workflows Partner with infrastructure and platform teams to manage cloud-native data environments (Snowflake, Spark, Delta Lake / Apache Iceberg) with a
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