Software Engineer II - Python, Big data

2 - 4 years

0 Lacs

Posted:4 days ago| Platform: Foundit logo

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Work Mode

On-site

Job Type

Full Time

Job Description

We have an exciting opportunity for you to advance your software engineering career and shape the future of technology.

Job summary

As a Software Engineer at JPMorgan Chase within the Corporate Technology, you work within an agile team to design and deliver trusted, market-leading technology products in a secure, stable, and scalable way. You are responsible for implementing critical technology solutions across multiple technical areas in support of the firm's business objectives.

Job responsibilities

  • Designs and develops creative software solutions and performs technical troubleshooting to solve complex problems
  • Creates secure, high-quality production code and reviews and debugs code written by others
  • Identifies opportunities to automate remediation of recurring issues to improve operational stability
  • Leads evaluation sessions with external vendors, startups, and internal teams to assess architectural designs and technical credentials
  • Collaborates with product managers, data scientists, machine learning engineers, and other stakeholders throughout the software development lifecycle
  • Adds to team culture of diversity, inclusion, and respect
  • Stays informed about advancements in large language models and generative AI, implementing new techniques and leveraging external APIs

Required qualifications, capabilities, and skills

  • Formal training or certification in software engineering concepts and 2+ years of applied experience
  • Strong skills in programming languages such as Python or Java
  • Experience developing and maintaining applications on public cloud platforms

Preferred qualifications, capabilities, and skills

  • Experience with big data technologies, preferably Spark and Databricks
  • Experience with Databricks platform
  • Proficiency in PySpark
  • Familiarity with AWS
  • Experience in automation and continuous delivery methods
  • Exposure to machine learning operations

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