Finance Data & AI Platform Lead

Apple Inc.; Austin (TX); On-site; USD 150,000 - 190,000; Full time

Job summary

Apple Inc. seeks an hands-on Data Engineering Manager to lead Finance Data & AI Foundation in Austin. You will design scalable financial data architectures on cloud platforms, ensuring performance and reliability while guiding a team of data and software engineers.

You’ll partner with Finance stakeholders to drive data-driven decisions and AI-enabled transformation. The role emphasizes execution, collaboration, and engineering discipline, with a focus on modernizing financial data systems that

Qualifications

• Bachelor’s degree in CS, IS, or equivalent.
• 8–12 years in data or software engineering.
• 5+ years in engineering management.
• Experience with data modeling, distributed data platforms, and best practices.

Responsibilities

• Lead design and development of scalable financial data architectures on cloud platforms.
• Apply SDLC practices to enforce modular architecture and resiliency.
• Prepare structured datasets for AI and support model training/deployment.
• Optimize data models and queries for large-scale financial datasets (SAP HANA, Singlestore, Iceberg).
• Collaborate with Finance users to deliver scalable solutions and mentor engineers.

Skills

Data modeling

Distributed data platforms

Software engineering best practices

Data transformation

Feature engineering

AI/ML readiness

Leadership/mentorship

Education

Bachelor's degree in Computer Science or equivalent

Tools

SAP HANA

Singlestore

Apache Iceberg

Job description

Apple Inc. seeks an hands-on Data Engineering Manager to lead Finance Data & AI Foundation in Austin. You will design scalable financial data architectures on cloud platforms, ensuring performance and reliability while guiding a team of data and software engineers.

You’ll partner with Finance stakeholders to drive data-driven decisions and AI-enabled transformation. The role emphasizes execution, collaboration, and engineering discipline, with a focus on modernizing financial data systems that