About the Role :

We are looking for a strong, hands-on Data Engineer with MLOps experience to join our team. This is a replacement role requiring someone who can hit the ground running, take ownership of data engineering projects, and collaborate effectively in a fast-paced, multi-platform environment.

Key Responsibilities :

- Design, build, and maintain scalable data pipelines across cloud platforms (primarily AWS and GCP)

- Solve complex data integration challenges using optimal ETL patterns from structured and unstructured data

- Develop and implement MLOps frameworks to automate deployment, monitoring, and lifecycle management of ML models

- Manage and optimize data models, with a focus on star schema design

- Orchestrate workflows using Apache Airflow and AWS Glue

- Validate data sources and ensure data integrity across pipelines

- Support CI/CD pipelines for ML model deployment

- Collaborate with cross-functional teams and communicate technical topics effectively

- Identify and resolve data incidents proactively

- Contribute to migration of systems from Azure/GCP to AWS

Required Skills & Experience :

- 5+ years of hands-on Data Engineering experience

- Strong proficiency in Python

- Experience with Apache Airflow

- Strong understanding of data modeling and star schema

- Hands-on experience with AWS

- Familiarity with GCP

- Experience with GitLab CI/CD and deployment pipelines

- Experience with ETL pipelines, monitoring, troubleshooting, and data validation

- Exposure to DBT is a plus

- Strong MLOps understanding and ML deployment experience

- Knowledge of scalable ML infrastructure and big data systems

Nice to Have :

- Apache Spark

- Azure Data Factory

- Deep AI/ML expertise

What We're Looking For :

- Strong data engineering fundamentals and practical problem-solving ability

- Clear verbal and written communication skills

- Fast learner who can adapt quickly to new tools and environments

- Ability to work independently and take ownership

- Someone proactive who asks the right questions

Shift Timing : 12 Noon IST onwards