Lead Software Engineer
Franklin Templeton (company site, opens in a new tab)10+ yrsHyderabadOn-siteDirect career pageEst. 30–45 LPA
Posted on 2 Sept
Reach people at Franklin Templeton
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at Franklin Templeton you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Lead architecture, development, and delivery of enterprise client mastering applications covering client onboarding, identity resolution, hierarchy management, survivorship, deduplication, and data quality.
- Design and implement scalable, secure APIs and services to distribute trusted client data across enterprise platforms, ensuring performance, stability, and compliance with architecture standards.
- Drive AI-assisted software engineering practices to enhance software delivery quality, engineer productivity, and operational efficiency.
Minimum Requirements
- 10+ years of enterprise software engineering experience in master data management, client mastering, data integration, or enterprise data platforms.
- Bachelor’s degree in Computer Science, Software Engineering, or related discipline; Master’s preferred.
- Proficient in Java, SQL, Spring Boot, Hibernate, React JS, Microservices, REST APIs, Oracle/MySQL, CI/CD automation, and AI-assisted development tools.
- Work shift: 2:00 PM to 11:00 PM IST.
Ideal Candidate Profile
- Experienced technical leader comfortable leading architecture and application design for scalable full-stack and API-driven platforms within enterprise data management.
- Familiar with AI-enabled software development lifecycle and applying AI techniques for data quality improvements and automation.
- Skilled at collaborating with diverse stakeholders to influence technology decisions and manage cross-functional dependencies in complex enterprise environments.