Finance Data Engineer

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 role requires working cross-functionally with business users ISu0026T data scientists and other engineers to develop and deploy data services and pipelines. An ability to acquire knowledge of Finance business processes is 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.

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.n Develop test deploy monitor document and troubleshoot data pipelines and feature-ready datasetsn 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 workflowsn Identify and review capabilities of emerging technologies and to enable the adoption of these new technologies and associated techniques

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

Effective Python shell and SQL programmernHands on experience with database design and architecture in cloud data warehouses (Snowflake) and lakehouse environments (s3)nAbility to implement end to end encryption and decryption policies as part of sensitive data pipelines and semantic views or other data sourcesnExperience with the data development lifecycle and its associated CI/CD and version control components and tooling (Jenkins Git Other)nExposure to cloud storage and orchestration tooling such as AWS and KubernetesnExperience with streaming interfaces and pipelines a plusnAbility to implement data and automation services via RESTful interfacesnAppreciation for data quality and validation in every pipelinenFinance and accounting process experience a plus