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.\\nThis 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.\\nYou 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 datasets\n 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\n 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 experience\n
Effective Python, shell and SQL programmer\nHands 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 sources\nExperience 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 Kubernetes\nExperience with streaming interfaces and pipelines a plus\nAbility to implement data and automation services via RESTful interfaces\nAppreciation for data quality and validation in every pipeline\nFinance and accounting process experience a plus
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
- Dice Id: 90733111
- Position Id: 4d56cdcabdd7c34f406c2e76edf4c016
- Posted 2 days ago
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