Senior Software Developer

Job description

At Franklin Templeton, we believe success is built through powerful partnerships. As a forward‑thinking asset manager, we build dynamic relationships with clients, understand their goals, and navigate complex markets together. We leverage cutting‑edge strategies and deep insights to unlock opportunities for long‑term wealth creation. Our talented, global teams bring expertise that is both broad and unique. From our welcoming, inclusive, and supportive culture to our globally diverse business, we offer opportunities not only to help you reach your potential, but also to contribute to our clients’ success. About The Department • The Product Data Services (PDS) team, part of Enterprise Data & Analytics, delivers trusted, scalable, and high-quality product data that powers investment, regulatory, client, digital, and analytics platforms across Franklin Templeton. The team builds cloud-native, API-driven data platforms using AWS, Snowflake, and modern lakehouse architectures to enable secure data access, high-performance analytics, and AI-driven innovation. Working in a highly collaborative environment, team members partner with product owners, architects, engineers, and business stakeholders while gaining exposure to enterprise-scale data platforms, cloud technologies, and next-generation AI-enabled data solutions. How You Will Add Value? Core Responsibilities • You will design and develop scalable data platforms on AWS and Snowflake. • You will build and optimize ETL/ELT pipelines and data products. • You will develop secure REST and GraphQL APIs for data access. • You will implement scalable data models and performance optimizations. • You will support data quality, monitoring, and governance frameworks. • You will integrate upstream data sources and downstream consumer platforms. • You will build reusable, maintainable, and high-performing engineering solutions. Team & Collaboration • You will collaborate with product owners, architects, and business stakeholders. • You will translate requirements into scalable technical solutions. • You will participate in Agile planning, estimation, and sprint delivery. • You will mentor junior engineers through code reviews and technical guidance. • You will contribute to engineering standards and best practices. Strategic Responsibilities • You will support AI-assisted data engineering and intelligent automation initiatives. • You will implement automated data quality and anomaly detection capabilities. • You will contribute to AI, Machine Learning (ML), and Large Language Model (LLM) integrations. • You will enhance observability, reliability, and platform efficiency. • You will modernize data platforms using cloud-native and lakehouse architectures. • You will promote automation and operational excellence across the platform. Production Support & Continuous Improvement • You will support production systems and incident resolution. • You will perform root cause analysis and corrective actions. • You will monitor platform performance and reliability metrics. • You will improve operational workflows through automation and optimization. What Will Help You Be Successful in This Role? Experience • 6+ years of data engineering experience building enterprise data platforms. • 3+ years of technical leadership or mentoring experience. • Experience building large-scale batch and near real-time data pipelines. • Experience working with cloud-native data platforms and lakehouse architectures. • Experience delivering solutions in Agile and cross-functional environments. Education & Certifications • Bachelor’s or Master’s degree in Computer Science, Engineering, or a related discipline. Technical Skills • AWS services including S3, EMR, Lambda, Glue, ECS/EKS, and IAM. • Snowflake, Apache Iceberg, and Delta Lake. • Python, SQL, Spark, PySpark, and dbt. • REST APIs, GraphQL, Microservices, and AppSync. • Airflow, Control-M, Docker, Kubernetes, GitLab, and CI/CD. • Dimensional Modeling, Lakehouse Modeling, Data Quality, and Lineage Frameworks. • Agentic AI, RAG, LLM Frameworks, and AI-assisted Data Engineering. Soft Skills • Strong analytical and problem-solving abilities. • Excellent communication and stakeholder management skills. • Ability to translate business requirements into technical solutions. • Strong collaboration and mentoring mindset. • Continuous learning and innovation focus. Preferred Qualifications • Experience with Kafka, Kinesis, or Spark Streaming. • Experience building AI/ML-ready datasets and feature stores. • Knowledge of investment management datasets and financial markets. • Familiarity with Data Mesh, Data Products, and self-service analytics. • Experience with observability and monitoring platforms. Work Shift Timings - 2:00 PM - 11:00 PM IST At Franklin Templeton, we believe your benefits should support your life, your goals, and your future. That’s why we offer a comprehensive Total Rewards package designed to help you thrive both personally and professionally. Highlights Of Our Benefits Include • Professional development growth opportunities through in-house classes and over 150 Web-based training courses • An educational assistance program to financially help employees seeking continuing education • Medical, Life and Personal Accident Insurance benefit for employees. Medical insurance also cover employee’s dependents (spouses, children and dependent parents) • Life insurance for protection of employees’ families • Personal accident insurance for protection of employees and their families • Personal loan assistance • Employee Stock Investment Plan (ESIP) • 12 weeks Paternity leave • Onsite fitness center, recreation center, and cafeteria • Transport facility • Child day care facility for women employees • Cricket grounds and gymnasium • Library • Health Center with doctor availability • HDFC ATM on the campus Franklin Templeton is an Equal