At Franklin Templeton, we’re driving our industry forward by developing new and innovative ways to help our clients achieve their investment goals. Our dynamic and diversified firm spans asset management, wealth management, and fintech, offering many ways to help investors make progress toward their goals. Our talented teams working around the globe bring expertise that’s both broad and unique. From our welcoming, inclusive, and flexible culture to our global and diverse business, we offer opportunities not only to help you reach your potential but also to contribute to our clients’ achievements.

Come join us in delivering better outcomes for our clients around the world!

About the department:

• The Enterprise Data, Governance & Integration Platforms Engineering team builds and manages foundational data, API, integration, and application platforms that enable scalable, secure, and reliable data, analytics, AI, and business solutions across the enterprise. The team develops cloud-native services, modern web applications, APIs, and reusable platform capabilities that accelerate data engineering, system integration, analytics, governance, and platform operations. Leveraging AWS, Azure, modern software engineering practices, CI/CD automation, and AI-assisted development, the team drives engineering productivity, platform adoption, and operational excellence. We partner closely with data, analytics, infrastructure, security, governance, and AI organizations to deliver enterprise-scale platform capabilities, hybrid cloud integrations, and enterprise-grade governance.

How you will add value?

• You will own the technical architecture and engineering direction for enterprise data platform frameworks, SDKs, and services.

• You will lead the design and delivery of reusable data engineering frameworks that accelerate ingestion, transformation, orchestration, and delivery across enterprise teams.

• You will architect scalable, event-driven platform components for batch and real-time data processing using AWS and Python.

• You will drive Data Lake and event-driven platform capabilities that enable self-service data engineering at enterprise scale.

• You will establish and enforce engineering standards for security, testing, observability, reliability, and governance across platform components.

• You will drive CI/CD automation through GitLab pipelines, Infrastructure as Code (Terraform), and deployment automation.

• You will mentor and develop senior engineers, fostering technical growth, architectural thinking, and platform engineering leadership.

• You will lead technical design reviews, architecture discussions, and cross-team technical alignment for data platform capabilities.

• You will champion AI-assisted development practices and Agentic AI workflows to improve platform engineering productivity and delivery velocity.

• You will design and refine system context, prompts, guardrails, and orchestration workflows that enable AI agents to execute complex engineering tasks reliably and securely.

• You will represent the data platform engineering team in leadership forums, steering committees, and architecture review boards.

• You will influence technical strategy and roadmap decisions across data engineering, analytics, and AI platform organizations.

What will help you be successful in this role?

Experience & Certifications:

• 9+ years of software engineering experience with progressive technical leadership responsibility in platform, framework, or infrastructure development.

• 3+ years building cloud-native solutions on AWS (Lambda, S3, Glue, AppSync, ECS/EKS, EventBridge, Kinesis, Step Functions, Airflow, DMS, Bedrock).

• Experience leading or mentoring engineering teams on data platforms or infrastructure projects.

• Proven experience designing and maintaining reusable frameworks, SDKs, or platform services adopted by multiple teams.

• AWS Solutions Architect or Data Analytics certification preferred.

• Bachelor’s degree in computer science, Engineering, or a related field (or equivalent practical experience).

Technical Skills:

• Strong Python development expertise includes object-oriented design, design patterns, and testing practices.

• Deep understanding of distributed systems, event-driven architectures, scalability, and performance optimization.

• Experience architecting Data Lake solutions, Apache Iceberg, or lake-house patterns at enterprise scale.

• Proficiency with CI/CD pipelines (GitLab preferred), Infrastructure as Code (Terraform), and deployment automation.

• Experience with containerization (Docker, Kubernetes) and microservices patterns.

• Hands-on experience with real-time streaming platforms (Kafka, Kinesis).

• Leverage Agentic AI development tools and coding agents to accelerate framework development, code generation, testing, and modernization

• Design and refine system context, prompts, guardrails, and orchestration workflows that enable AI agents to execute complex engineering tasks reliably and securely

• Integrate AI-enabled development practices into platform engineering, CI/CD pipelines, and developer workflows while maintaining enterprise security and quality standards

• Drive adoption of AI-powered engineering capabilities that improve developer productivity and delivery velocity.

• Experience with observability platforms (CloudWatch, Datadog, OpenSearch).

• Java development experience as a secondary language.

Leadership Skills:

• Proven ability to lead and influence cross-functional teams including engineers, architects, data engineers, and product stakeholders.

• Experience establishing architectural governance, engineering standards, and technical decision-making frameworks.

• Track record of mentoring senior engineers and driving technical growth across teams.

• Strong stakeholder management with the ability to influence technical and non-technical leadership.

• Experience driving platform adoption, evangelizing engineering capabilities, and building developer communities.

• Ability to define technical vision and translate business requirements into scalable platform strategies.

• Experience leading technical modernization, platform migration, or large-scale engineering transformation initiatives.

Soft Skills:

• Systems-thinking and architectural mindset with a passion for building developer-facing platforms.

• Strong analytical thinking and creative problem-solving skills.

• Excellent communication and collaboration across engineering, product, and executive leadership teams.

• Continuous learner with enthusiasm for AI, cloud-native technologies, and emerging engineering practices.

• Thrives in fast-paced, high-accountability environments with ownership over delivery outcomes.

• Collaborative and ownership-driven mindset with a bias for action.

Technical Domain:

Core:

• Advanced Python • AWS • Distributed Systems • Event-Driven Architecture • Framework & SDK Development • CI/CD • Infrastructure as Code • Platform Architecture.

AWS Services:

• S3 • Lambda • Glue • EMR • ECS/EKS • EventBridge • Kinesis • Step Functions • Bedrock • Athena • DynamoDB • OpenSearch • IAM

Platform & Tooling:

• GitLab CI/CD • Terraform • Docker • Kubernetes • Airflow • Data Lake (Iceberg) • Observability & Monitoring

AI & Automation:

• AI Coding Agents • Agentic AI Development • Prompt Engineering • AI Guardrails & Orchestration • AI-Enabled CI/CD

Work Shift Timings - 2:00 PM - 11:00 PM IST