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JPMorgan Lead Software Engineer - Java microservices kafka AWS 
India, Karnataka, Bengaluru 
660694804

09.09.2025

Bring your engineering skills to the next level where your expertise will drive the development of cutting-edge Data, Analytics, and AI/ML Platforms.

Job responsibilities

  • Implements and builds firm-wide Data and AI platforms on cloud/on-premise with distributed computing and emerging technologies.
  • Develops secure and high-quality production code, and review and debug code written by others.
  • Contributes through the full software development lifecycle, including architecture, proofs of concept, prototyping, development, rollout, and support.
  • Prioritizes solving customer requests and issue reports and take part in support coverage.
  • Actively contributes to the engineering community as an advocate of firm-wide frameworks, tools, and practices of the Software Development Life Cycle.
  • Collaborates with cross-functional teams to align platform capabilities with business needs and strategic goals.

Required qualifications, capabilities, and skills

  • Formal training or certification on software engineering concepts and 5+ years applied experience

  • Hands-on professional experience in building complex/large-scale Data and AI Platforms in both private and public cloud environments (e.g., AWS).
  • Degree in Computer Science, Computer Engineering, Mathematics, or a related technical field.
  • Advanced knowledge of software applications and technical processes with considerable in-depth knowledge of application, data, cloud, and infrastructure architecture disciplines.
  • Advanced hands-on skills in Java and/or Python programming.
  • Extensive hands-on experience with Databricks/Unity Catalog, Snowflakes, AWS RedShift, AWS Athena, Glue, Lakeformation, Kafka, PostgreSQL, and NoSQL (Cassandra, MongoDB).
  • Hands-on experience with DevOps (CI/CD) practices, including Terraform; Containers and cloud ability, including Docker, Kubernetes, etc.
  • Ability to tackle design and functionality problems independently. A self-starter who thrives in a fast-paced, agile setting.
  • Clear and effective verbal and written communication skills and the ability to communicate seamlessly across business, product, tech and data scientist teams.

Preferred qualifications, capabilities, and skills

  • Hands-on experience in building ETL/Data Pipeline and data platforms (e.g., Databricks, Spark/Hadoop, and Snowflake).
  • Knowledge of workflow orchestration tools (e.g., Apache Airflow), integration technologies (e.g., GraphQL, REST), open table formats (e.g. Apache Iceberg, Delta Lake), data security & access control (coarse-grained vs fine-grained)
  • Experience building AI/ML/GenAI applications, deploying Machine Learning models, and MLOps/LLMOps Lifecycle