Summary
Posted: Sep 13, 2024
Weekly Hours: 40
Role Number:200567456
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.
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 interfaces • Collaborate with other engineers to define and adopt best practices for data and machine learning engineering • Identify and review capabilities of emerging technologies and to enable the adoption of these new technologies and associated techniques
Minimum Qualifications
- 5+ more years of experience within Data Engineering
- Undergraduate degree in Computer Science, MIS, Engineering, Mathematics or other quantitative discipline
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
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Job Features
Job Category | Engineering |
Job Reference ID | 200567456 |
Job Location | Austin, Texas, United States |