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.

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 Schedule & Location:

- Location: Hyderabad, India

- Shift Timings: 2 PM to 11 PM IST