Software Engineer III - Big Data, AWS, Spark - Data Engineering
Software Engineer III - Big Data, AWS, Spark - Data Engineering
JP Morgan Chase & Co.Early Applicant
- Posted 20 hours ago
- Be among the first 10 applicants
Job Description
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 Corporate Technology, you serve as a seasoned member of an agile team to design and deliver trusted market-leading technology products in a secure, stable, and scalable way. You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm's business objectives.
Job responsibilities
As a Software Engineer III at JPMorganChase within Corporate Technology, you serve as a seasoned member of an agile team to design and deliver trusted market-leading technology products in a secure, stable, and scalable way. You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm's business objectives.
Job responsibilities
- Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or breakdown technical problems,
- Develop workflows and ETL data pipelines using Bigdata, Spark, AWS
- Build, test, and maintain scalable data pipelines and data architectures that support enterprise analytics use cases
- Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems
- 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.
- Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development
- Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems
- Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture
Required qualifications, capabilities, and skills
- A. Formal training or certification on software engineering concepts and 7+ years applied experience.
- Hands-on experience with Bigdata, Spark, AWS and SQL
- Knowledge of cloud platforms (AWS) and distributed data processing
- Hands-on practical experience in system design, application development, testing, and operational stability
- Ability to collaborate effectively within agile teams and across stakeholders
- Hands-on practical experience in system design, application development, testing, and operational stability
- Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages
- 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.
- Overall knowledge of the Software Development Life Cycle
- Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
Preferred qualifications, capabilities, and skills
- Familiarity with Databricks.
- Exposure to cloud technologies
More Info
Job Type:
Function:
Employment Type:
Key Skills
AI-assisted software development tools
Application Resiliency
Bigdata
About Company
Skills:
Software Development Life Cycle, Sql, AWS, Bigdata, Agile Methodologies, Spark, AI-assisted software development tools, Data engineering best practices
Skills:
bedrock , Machine Learning, Agile Methodologies, Scikit Learn, Sql, Tensorflow, Git, MLops, Pytorch, Rest Apis, Python, AWS, Generative AI, Prompt engineering, Pinecone, OpenSearch, LangGraph, SageMaker, microservices architecture, LLM APIs, FAISS, OpenAI integration, RAG architectures
Skills:
Angular.js, CSS, Serverless Computing, Containers, Node.js, Spring Cloud, Javascript, Spring Boot, AWS, Cloud-native development principles, API and Microservices-based architecture, Netflix OSS
Skills:
S3, Apis, Aws Services, Roles, Node.js, Vpc, Jira, Svn, Lambda, Ec2, Confluence, Cloudwatch, Aws Cli, Iam, Authentication, Api Gateway, Policies, Authorization, SDKs
Skills:
Java Programming Language, Agile Methodologies, Spring Boot, Sql, Spring Cloud, Nosql, Web Services, Docker, Logging tools, Restful Apis, Azure, Kubernetes, AWS, Microservices architecture, Security best practices, CI CD tools