Sr. Lead Software Engineer - Java, Data, OpenAPI/Swagger, Kafka

JPMorganChase; Bengaluru; On-site; INR 1,800,000 - 3,000,000; Full time

Job summary

JPMorgan Chase in Bengaluru, India, invites a Sr. Lead Software Engineer to join the Post Trade Technology team. You will drive data quality and safety, partner with the Data & Analytics leads, and oversee AI-assisted engineering practices across teams.

You will work with product data owners to ensure data supports analytics outcomes while following firmwide data policies. The role emphasizes governance, secure coding, and scalable data delivery, with collaboration across business, technology,

Qualifications

• Formal training or certification on software engineering concepts.
• Experience in data technology including governance and data management.
• Proven use of enterprise AI-assisted development tools with focus on correctness, performance and security.

Responsibilities

• Create plans for developing and delivering product data to support objectives, operations, analytics and reporting.
• Collaborate with partners to understand data and its business use; provide SME on data content and usage.
• Drive adoption and governance of AI-assisted engineering practices to improve code quality, speed, and reliability.
• Apply knowledge of SDLC tools, including AI-assisted development, to scale value from automation.
• Identify and document the scope, meaning, purpose, and classification of critical product data with metadata.
• Support Data & Analytics teams by identifying data needed for analytics platforms.
• Document data accuracy, timeliness, and influence resources to resolve data issues.
• Develop processes to identify, monitor, and mitigate data risks (protection, retention, storage, use).
• Manage tasks to comply with firmwide data policies and standards.
• Build relationships with product data delivery partners and stakeholders across business, technology, analytics, operations, risk and control.
• Track milestones, risks, bottlenecks, workstreams, KPIs, and staff for data-related deliveries.

Skills

Software engineering

Data governance

AI-assisted development tools

Secure coding

APIs (OpenAPI/Swagger, REST, GraphQL)

Event-driven architectures (Kafka)

Data privacy & regulatory knowledge

Analytical skills

Communication

Education

Bachelor's degree in a relevant field

Job description

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 Sr. Lead Software Engineer at JPMorgan Chase within the Commercial & Investment Bank's Post Trade Technology team , you will also be accountable for identifying and mitigating data risks throughout the data life cycle in compliance with Firmwide policies and standards. You will serve as a member of the product team, collaborating with the Product Owner, design, and technology leads to ensure that the product delivers data in a manner consistent with the quality and safety requirements of the business. You will also partner with their aligned Data & Analytics lead to drive increased business value through the identification of data required to support analytics outcomes.

Job Responsibilities

• Create plans for developing and delivering product data to support strategic objectives, operations, analytics, and reporting.
• Collaborate with key partners to drive understanding of data and its business use and Provide subject matter expertise on product data content and usage within the business area.
• Drives adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patterns and automation within the SDLC/TLM toolchain.
• Applies knowledge of tools within the Software Development Life Cycle toolchain, including approved AI-assisted development and automation capabilities, to improve the value realized by automation at scale.
• Identify and document the scope, meaning, purpose, and classification of critical product data with appropriate metadata.
• Support Data & Analytics leads by identifying data needed for integration into analytics platforms for projects.
• Document and coordinate requirements for data accuracy, completeness, and timeliness and Influence resources to resolve data issues promptly.
• Develop processes to identify, monitor, and mitigate data risks, including protection, retention, destruction, storage, use, and quality.
• Manage tasks to comply with firmwide policies, standards, and procedures for data integrity and protection.
• Build relationships with product data delivery partners and consumers, including leaders in Business, Technology, Analytics, Operations, Risk, and Control.
• Track and manage milestones, risks, bottlenecks, workstreams, KPIs, and staff to ensure successful data-related deliveries.

Required Qualifications, Capabilities, And Skills

• Formal training or certification on software engineering concepts and 5+ years applied experience
• Experience in a data technology including data governance and data management
• Demonstrated experience leading effective use of enterprise-authorized AI-assisted software development tools within the work environment (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 senior engineers/leads on compliant usage patterns and controls.
• Strong understanding of API concepts, lifecycle, and documentation (OpenAPI/Swagger, REST, GraphQL).
• Experience in event-driven architectures or messaging platforms (e.g., Apache Kafka)
• Knowledge of data privacy, security, and regulatory requirements relevant to financial services.
• Strong analytical, organizational, and problem-solving skills. Proficient in data analysis tools;
• Demonstrated ability to manage delivery timelines, and ensure our product and organization is on track to meet our goals
• Excellent written and verbal communication skills and ability to work collaboratively with technical and business stakeholders.

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