Software Engineer III - AWS BIG Data Engineer
- LocationBengaluru, Karnataka, India
- Work typeNot stated
- EmploymentFull-time
- Posted6 November 2026
- SourceJPMorganChase's careers page (Oracle Recruiting)
Live checkFirst seen 7 h ago; still listed on JPMorganChase's careers page 3 h ago.
Moves fastWhen JPMorganChase takes a role down early, it is usually about 4 days after posting. Apply soon.
At a glance
- Experience3+ years
- Skills and toolsSpark, AWS, EHR, SQL, CI/CD, Git, Jira
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Check my fitAbout the role
We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.
As a Software Engineer III at JPMorganChase within the Commercial and Investment Bank Technology and Wholesale Client Profitability within PGBT organization, you are responsible for designing and developing software solutions to support the Wholesale Client Profitability (WCP) platform in a stable, scalable manner. You will be required to apply your depth of knowledge and expertise to all aspects of the software development lifecycle, as well as partner with stakeholders to stay focused on common goals. You will work in a collaborative, trusting, thought-provoking environment; one that encourages diversity of thought and creative solutions that are in the best interests of our customers globally.
Job Responsibilities:
- Understands the skills for data modelling, using cloud data warehouses, working with business intelligence tools,
- Delivers creative software solutions and design, with the ability to think beyond routine or conventional approaches
- Analyzes, develops, tests and supports cloud, big data and reporting solutions required to fulfil business and technology requirements
- Troubleshoots technical issues by breaking down problems and ensuring permanent resolution
- Generates reports, test outputs, maintain documentation and controls, use fit-for-purpose data, and help ensure reports are complete, accurate, and timely.
- Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity across complex deliverables (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards; contributes learnings and reusable patterns to improve broader team effectiveness.
- Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation
- Identifies opportunities to eliminate or automate manual processes and recurring issues to improve the overall operational stability of the platform
- Adds to team culture of diversity, opportunity, inclusion, and respect
Required qualifications, capabilities, and skills:
- Formal training or certification on software engineering concepts and 3+ years applied experience.
- Hands-on practical experience in system design, application development, testing, and operational stability.
- Ability to work in collaborative teams to achieve organizational goals.
- Proven technical proficiency in Big data stack – HDFS, Spark, Impala, etc. with expertise in AWS including S3, EMR, SQS, etc.
- Experience in some Industry Standard Reporting Tool like Cognos/Sigma/Thoughtspot etc. with knowledge in Advanced SQL and data management.
- Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security.
- Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices.
- Strong understanding of data, data modeling and database methodologies and architecture disciplines.
- Ability to identify opportunities to automate workflows, implementing based on specific use cases with solid understanding of agile methodologies such as CI/CD, application resiliency, and security.
- Exceptional interpersonal, relationship and communication skills with proficiency in all aspects of the Software Development Life Cycle.
Preferred qualifications, capabilities, and skills:
- Working knowledge of DevOps is desirable, but not mandatory
- AWS Cloud Certification and other relevant certifications are a plus
- Exposure to Git, maven, sonar and JIRA desirable.
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