Software Engineer III-Databricks, Spark/PySpark, AWS
JPMorgan Chase · Hyderabad, India · 23h ago
SeniorOn-siteSoftware Engineering
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 & Investment Bank Payments Technology team, 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 the Commercial & Investment Bank Payments Technology team, 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
- 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
- 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 - Strong hands-on expertise in Databricks and Spark/PySpark, including deep performance optimization experience.
- Strong hands-on experience with AWS cloud-native implementation (storage, compute, IAM/security, networking) and production engineering practices.
- Strong proficiency in Python and SQL, including advanced query design, optimization, and data validation.
- Proven experience building and managing data models and operating production-grade ETL/ELT systems.
- Demonstrated AI/ML experience (supporting model training/inference, feature engineering pipelines, or MLOps practices).
- Proven leadership/SME capability: mentoring, driving engineering standards, and making sound technical decisions based on business needs.
- 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
Preferred qualifications, capabilities, and skills
- Familiarity with modern front-end technologies
- Exposure to cloud technologies
- Experience with Delta Lake, Unity Catalog, Structured Streaming, and orchestration tools (e.g., Airflow)
- Familiarity with MLflow, feature stores, model serving, or LLM/GenAI-enabled applications
- Experience with IaC (Terraform/CloudFormation), Docker/Kubernetes, and monitoring/logging toolsets