Lead Software Engineer - Data Engineer

JPMorgan Chase & Co.; Hyderabad; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

JPMorganChase is seeking a Lead Software Engineer to join the Consumer and Community Banking Technology team in Hyderabad. You will lead the design and delivery of scalable data platforms, leveraging AI-assisted engineering practices to improve code quality, security, and velocity.

Responsibilities include building data pipelines with Spark, Kafka, Flink, and AWS services, applying IaC, and shaping data architecture for batch and real-time processing at enterprise scale.

Qualifications

• 5+ years of software engineering experience in data engineering or adjacent roles.
• Experience leading AI-assisted software development tools and practices.
• Strong understanding of responsible AI in engineering and secure handling of data.

Responsibilities

• Build automated data operations using AI-driven workflows for monitoring, optimization, and remediation.
• Design and deploy data solutions using AWS services (S3, Lambda, EKS, Step Functions).
• Implement IaC for reproducible deployments and scalable environments.
• Promote enterprise-approved AI-assisted engineering practices and secure coding standards.
• Develop scalable data ingestion, transformation, and analytics using Spark, Glue, Iceberg, Kafka, and Flink.
• Architect end-to-end data solutions from ingestion to analytics at enterprise scale.
• Define data architecture standards for batch and real-time pipelines.

Skills

5+ years experience

AI-assisted development

DataOps

Data ingestion/transform analytics

Python/Scala/Java

SQL

AWS services (S3, Lambda, EKS, Step Fn

Apache Spark

Apache Kafka

Apache Flink

Tools

AWS S3

AWS Lambda

AWS EKS

AWS Step Functions

Apache Spark

Apache Iceberg

Apache Kafka

Apache Flink

Job description

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.

As a Lead Software Engineer at JPMorganChase within the Consumer and community banking technology team, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way.

Job responsibilities

• Build automated, self-healing data operations using agentic frameworks and AI-driven workflows for intelligent monitoring, optimization, and remediation
• Design and deploy data solutions using AWS services including S3, Lambda, EKS (Elastic Kubernetes Service), and Step Functions
• Implement Infrastructure as Code (IaC) practices for reproducible and scalable deployments
• Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
• 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.
• Build and optimize scalable data ingestion, transformation, and analytics solutions using Apache Spark, AWS Glue, and Apache Iceberg
• Develop and manage both batch and real-time data pipelines leveraging Apache Kafka and Apache Flink for streaming data processing. Implement Data Lake architectures with efficient data organization, partitioning, and governance strategies
• Design and architect end-to-end data solutions from ingestion to analytics, ensuring scalability, reliability, and performance at enterprise scale
• Define data architecture standards and best practices for batch and real-time data processing pipelines

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years applied experience
• Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
• Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices
• Experience with modern data engineering practices including DataOps, data observability, and data governance
• Deep expertise in data ingestion, transformation, and analytics using Apache Spark, AWS Glue, Apache Iceberg, and Data Lake architectures
• Proven experience designing and managing batch and real-time data pipelines with Apache Kafka and Apache Flink
• Strong hands-on experience with AWS cloud services including S3, Lambda, EKS, and Step Functions
• Experience building automated solutions using agentic frameworks and AI-driven workflows for intelligent data operations
• Advanced proficiency in programming languages such as Python, Scala, or Java with strong SQL skills
• Demonstrated ability to architect end-to-end data solutions from ingestion to analytics at scale