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:
Analytics Engineering enables enterprise-scale advanced analytics and machine learning capabilities across business domains. The team works closely with data scientists, analysts, and engineering teams to deploy scalable data products and models into production. By maintaining strong governance, security, and compliance standards, the team delivers trusted analytics solutions that support business decision-making and innovation.
How You Will Add Value?Core Responsibilities:
You will build and maintain data pipelines for analytics solutions.
You will create data transformations and curated datasets.
You will support feature engineering and feature store pipelines.
You will assist with Machine Learning Operations (MLOps) workflows.
You will prepare model data and support monitoring activities.
You will contribute to Continuous Integration/Continuous Deployment (CI/CD) processes.
You will perform data validation, quality checks, and lineage tracking.
Team & Collaboration:
You will collaborate with engineers, analysts, and data scientists.
You will support automation initiatives and agentic workflows.
AI Fluency & Modern Engineering Productivity:
You will use Artificial Intelligence (AI) tools to improve development productivity.
You will leverage AI for coding, testing, and documentation.
You will use AI-assisted troubleshooting to optimize query performance.
You will gain experience with AI-powered automation solutions.
Experience, Education & Certifications:
2–4 years of experience in data or analytics engineering.
Bachelor’s degree in computer science, Engineering, or a related discipline.
Exposure to Amazon Web Services (AWS) cloud services.
Understanding of Extract, Transform, Load / Extract, Load, Transform (ETL/ELT) concepts.
Interest in learning MLOps and analytics platform technologies.
Technical Skills:
Working knowledge of Structured Query Language (SQL), Python, and data processing.
Familiarity with data quality and validation practices.
Basic understanding of DevOps and CI/CD principles.
Exposure to Apache Airflow or similar orchestration tools.
Understanding of streaming data concepts.
Exposure to AI, Machine Learning (ML), or Generative AI (GenAI) projects.
Soft Skills:
Strong analytical and problem-solving abilities.
Effective verbal and written communication skills.
Interest in automation, innovation, and continuous learning.
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 Opportunity Employer. We are committed to providing equal employment opportunities to all applicants and existing employees, and we evaluate qualified applicants without regard to ancestry, age, color, disability, genetic information, gender, gender identity, or gender expression, marital status, medical condition, military or veteran status, national origin, race, religion, sex, sexual orientation, and any other basis protected by federal, state, or local law, ordinance, or regulation.
Skills Required
- 2-4 years of experience in data or analytics engineering
- Bachelor's degree in computer science, engineering, or a related discipline
- Exposure to Amazon Web Services cloud services
- Understanding of ETL/ELT concepts
- Working knowledge of SQL, Python, and data processing
- Familiarity with data quality and validation practices
- Basic understanding of DevOps and CI/CD principles
- Exposure to Apache Airflow or similar orchestration tools
- Understanding of streaming data concepts
- Exposure to AI, machine learning, or Generative AI projects
- Strong analytical and problem-solving abilities
- Effective verbal and written communication skills
Franklin Templeton Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Franklin Templeton and has not been reviewed or approved by Franklin Templeton.
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Retirement Support — Retirement programs, including a notably strong 401(k) match and access to an employee stock purchase option, are positioned as key strengths. These features are described as meaningful contributors to total compensation.
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Leave & Time Off Breadth — Flexible work arrangements, paid volunteer time, and a defined paid parental leave minimum support strong work–life balance. Time-off breadth is frequently highlighted as a bright spot in the overall package.
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Strong & Reliable Incentives — A bonus structure that pays out regularly and a pay-for-performance philosophy add meaningful upside to cash compensation. Incentives can be particularly impactful in certain functions and levels.
Franklin Templeton Insights
What We Do
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