Compute Infrastructure Platforms Lead Data Engineer
JPMorgan Chase
- Location
- LONDON, United Kingdom
- Work model
- On-Site
- Level
- Senior
- H-1B history
- 1,524 approvals (FY2023)
- Posted
- 18h ago
Skills
About this role
Join us as we embark on a journey of collaboration and innovation, where your unique skills and talents will be valued and celebrated. Together we will create a brighter future and make a meaningful difference. As a Lead Data Engineer at JPMorganChase within the [insert LOB or sub LOB], you are an integral part of an agile team that works to enhance, build, and deliver data collection, storage, access, and analytics solutions in a secure, stable, and scalable way. As a core technical contributor, you are responsible for maintaining critical data pipelines and architectures across multiple technical areas within various business functions in support of the firm’s business objectives.
Job responsibilities
Ensures consumers are able to have a high level of trust in the analysis they produce based on the data our product line emits. Generates data models for their team using firmwide tooling, linear algebra, statistics, and geometrical algorithms Delivers data collection, storage, access, and analytics data platform solutions in a secure, stable, and scalable way Implements database back-up, recovery, and archiving strategy Evaluates and reports on access control processes to determine effectiveness of data asset security with minimal supervision Adds to team culture of diversity, opportunity, inclusion, and respect Required qualifications, capabilities, and skills Working knowledge of Infrastructure Platforms and Enterprise Server Operating Systems Working experience with both relational and NoSQL databases Experience and proficiency across the data lifecycle Experience with database back-up, recovery, and archiving strategy Preferred qualifications, capabilities, and skills Proven experience working in SRE or Infrastructure Deployment roles, Mid level data pipeline or analytical product creation Proven Data Quality issue root cause analysis