Associate Software Engineer

Franklin Templeton Investments; Hyderabad; On-site; INR 800,000 - 1,400,000; Full time

Benefits offered by this job

Educational assistance

ESOP

Health insurance

Onsite facilities

Job summary

Franklin Templeton Investments in Hyderabad is seeking an Analytics Engineer to design and maintain data pipelines, support ML workflows, and collaborate with data scientists.

The role requires 2–4 years of experience, a CS/engineering degree, and hands-on AWS and Airflow exposure. You will contribute to CI/CD, data quality, and scalable analytics solutions. The team emphasizes learning and development.

Qualifications

• 2–4 years of experience in data or analytics engineering.
• Bachelor’s degree in computer science, engineering, or a related discipline.
• Exposure to AWS cloud services and data platforms.
• Understanding ETL/ELT concepts and data governance.

Responsibilities

• Build and maintain data pipelines for analytics solutions.
• Create data transformations and curated datasets.
• Support feature engineering and feature store pipelines.
• Assist with MLOps workflows and model data preparation.
• Contribute to CI/CD processes and data validation.
• Ensure data quality and lineage tracking.

Skills

SQL

Python

Data processing

AWS

Airflow

GenAI / AI tools

CI/CD basics

Education

Bachelor's degree in computer science, engineering, or related discipline

Tools

Apache Airflow

ETL/ELT concepts

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

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.

What Will Help You Be Successful in This Role

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

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

Benefits

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

Equal Opportunity

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.