Software Engineer – Big Data and Cloud

JPMorgan Chase
JPMorgan Chase

Job Overview

Job Description

Cloud Big data platform is a team responsible for architecting, designing and implementing a new, cutting edge, cloud platform for transforming our business applications into scalable, elastic systems that can be instantiated on demand, on cloud.

The role calls for the Engineer to design, develop, configure, test, debug and document all layers of the Cloud stack to satisfy the new big data system requirements. This is expected to range from Cloud hosting platform to the design and implementation of higher level services such as the IaaS, PaaS and SaaS layers, big data platform and services. The focus of this role is on the product and service for cloud big data platform.

The ideal candidate should be comfortable being directly involved with the design, development, testing, and operation of the solutions that will be composed into the Cloud Services environment. Once implemented, the candidate will typically be expected to provide some higher level production and technical support in the case of a serious outage. They will also provide comprehensive consultation to business unit and IT management and staff at the highest technical level. They will work closely with Cloud Services management to identify and specify complex business requirements and processes that drive the platform roadmap. Additionally, they will research and evaluate alternative solutions and make recommendations for changes that would enhance the platform.

Responsibilities shall include:

  • Work as part of the team to ensure appropriate business measures are defined and documented
  • Create cloud and big data technical design recommendations for developing and integrating new software and system technologies – from the physical layer through to the virtual layer – per written specifications; test, evaluate, engineer, implement and support said technologies
  • Evaluate service level issues and suggested enhancements escalated by support to diagnose and address underlying system problems and inefficiencies – engage third party suppliers on support issues as required
  • Review and influence new and evolving design, architecture, standard, and methods for operating services and systems
  • Respond to and resolve emergent service problems; build tools and automation to prevent problem recurrence
  • Participate in software and system performance analysis and tuning, service capacity planning and demand forecasting
  • Drive technical innovation and efficiency in infrastructure operations via automation – for example automated server build processes
  • Create processes that enhance operational workflow and provide positive customer impact
  • Design systems management solutions using automation and self-repair rather than relying on alarming and human intervention
  • Avoid re-inventing the wheel and prefer appropriately simple, repeatable solutions over more complex and failure prone ones
  • Develop tools and utilities to provide short term solutions to immediate needs as required

Preferred skill sets

  • Excellent documentation and communication skills – needs to be able to clearly articulate complex IaaS / PaaS / SaaS concepts to people new to Cloud and Big Data Engineering
  • Strong analytical and troubleshooting skills – desire to solve complex problems at scale
  • Software engineering, system administration, systems engineering, network engineering
  • Strong Data Services expertise – Databases, Messaging, Caching, Big Data solutions
  • Strong Programming skills – needs to be able to code, leverage APIs, and understand security, authentication and data structures.
  • Highly proficient in at least one programming language such as python, perl, shell, java, c#
  • Good knowledge of networking, security, DNS, Unix/Linux operations and troubleshooting, on AWS, Azure or GCP.
  • Understanding of how commodity servers, operating systems and networks function, perform and scale
  • Minimum 2-5 years software Engineering / Development experience
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