Apple

Designs phones, computers and their operating systems

Finance Data Engineer

Data EngineeringConfirmed live in the last 24 hours

Full-timeNo salary listedIn-person

About the Job

Requirements

At least five years of relevant data engineering experience.
An undergraduate degree in Computer Science, Management Information Systems, Engineering, Mathematics, or another quantitative discipline, with five or more years of experience.
Program effectively in Python, shell, and SQL.
Have hands-on experience with database design and architecture in cloud data warehouses such as Snowflake and lakehouse environments such as Amazon S3.
Implement end-to-end encryption and decryption policies as part of sensitive data pipelines and semantic views or other data sources.
Have experience with the data development lifecycle and its associated continuous integration/continuous delivery and version control components and tooling, such as Jenkins and Git.
Have exposure to cloud storage and orchestration tooling such as Amazon Web Services and Kubernetes.
Implement data and automation services via RESTful interfaces.
Appreciate data quality and validation in every pipeline.

Responsibilities

Work cross-functionally with business users, Information Systems and Technology, data scientists, and other engineers to develop and deploy data services and pipelines.
Work in enterprise data warehouse and lakehouse environments to identify and combine data efficiently and scalably to answer business questions.
Work closely with data scientists, machine learning engineers, software engineers, and business partners to identify, capture, collect, load, and format data from external sources, internal systems, and the data warehouse.
Develop, test, deploy, monitor, document, and troubleshoot data pipelines and feature-ready datasets.
Collaborate with other engineers to define and adopt best practices for translating finance use cases into data requirements, schemas, and retrieval patterns for retrieval-augmented generation, agents, and other large language model workflows.
Identify and review capabilities of emerging technologies and enable the adoption of new technologies and associated techniques.
Acquire knowledge of Finance business processes.

Desired Qualifications

Experience with streaming interfaces and pipelines is a plus.
Finance and accounting process experience is a plus.

Summary

The Finance Data Engineer is a technical expert who creates data interfaces, pipelines and codebase that drives innovative data products for Apple Finance. They build reliable, accurate, consistent, and architecturally sound solutions that are aligned with business needs. This role requires working cross-functionally with business users, IS&T, data scientists and other engineers to develop and deploy data services and pipelines. An ability to acquire knowledge of Finance business processes is important. You will be working in an enterprise data warehouse and lakehouse environments to help identify and combine data in an efficient, scalable manner to help answer business questions.

Minimum Qualifications

5+ years of relevant Data Engineering experience Undergraduate degree in Computer Science, MIS, Engineering, Mathematics or other quantitative discipline required with five or more years of experience

Preferred Qualifications

Effective Python, shell and SQL programmer Hands on experience with database design and architecture in cloud data warehouses (Snowflake) and lakehouse environments (s3) Ability to implement end to end encryption and decryption policies as part of sensitive data pipelines and semantic views or other data sources Experience with the data development lifecycle and its associated CI/CD and version control components and tooling (Jenkins, Git, Other) Exposure to cloud storage and orchestration tooling such as AWS and Kubernetes Experience with streaming interfaces and pipelines a plus Ability to implement data and automation services via RESTful interfaces Appreciation for data quality and validation in every pipeline Finance and accounting process experience a plus

Description

• Work closely with data scientists, machine learning engineers, software engineers, and business partners to identify, capture, collect, load and format data from the external sources, internal systems and the data warehouse. • Develop, test, deploy, monitor, document and troubleshoot data pipelines and feature-ready datasets • Collaborate with other engineers to define and adopt best practices for translate finance use cases into data requirements, schemas, and retrieval patterns for RAG, agents, and other LLM workflows • Identify and review capabilities of emerging technologies and to enable the adoption of these new technologies and associated techniques

About the Company

Apple

Designs phones, computers and their operating systems

Apple designs and sells consumer electronics, from iPhone smartphones and Mac computers to tablets and wearable devices. Its operating systems manage apps and built-in functions for communication and work, while iCloud stores files and synchronizes data across devices. Customers buy additional digital services through subscriptions such as Apple Music and Apple TV, and developers distribute software through the App Store. Apple earns money from hardware sales, subscriptions and digital transactions, selling directly to customers and through retailers and mobile carriers around the world. It was founded in 1976 and has its headquarters in Cupertino, California.

Company size: 10,001+
Company stage: IPO
Headquarters: Cupertino, CA
Founded: 1976

Recently Posted Jobs

Explore more opportunities at Apple

See more jobs