Job Title: Data Engineer II
Location: Gurgaon, HR
Experience Required: 3+ years
Role Type: Contract-5 months
Shift: general
Work Mode: Hybrid
CTC-18 LPA

Mandate skills:
• Python
• PySpark / Spark
• AWS – S3, SageMaker, Lambda, EKS, EMR, Glue, Athena
• MLOps / ML Model Deployment & Inference
• Docker & Kubernetes
• Terraform / IaC
• CI/CD

About The Job:
Company Name: VARITE India Private Limited

About The Client:
An American technological research and consulting firm based in Stamford, Connecticut that conducts research on technology and shares this research through private consulting, executive programs, and conferences. Its clients include large corporations, government agencies, technology companies, and investment firms.
The Client serves over 12,000 organizations in over 100 countries with an employee strength of 15,000.

About The Job:
• Client is seeking a talented and passionate MLOps Engineer to join our growing team.
• Responsible for building Python- and Spark-based ML solutions that ensure the reliability, scalability,



and efficiency of machine learning workloads in production.
• Collaborate closely with data scientists, data engineers, and software engineers to operationalize ML models and optimize MLOps workflows.
• Leverage expertise in Python, Spark, ML model inferencing, AWS, and cloud-native technologies to drive data-driven initiatives.
Essential Job Functions:
MLOps Infrastructure & Automation:
• Design, implement, and maintain scalable and reliable MLOps pipelines on AWS.
• Automate ML model inferencing, deployment, monitoring, retraining, and maintenance workflows.
• Build and maintain Infrastructure as Code (IaC) using Terraform or equivalent tools.
• Implement and manage CI/CD pipelines for API, ML model, and infrastructure deployments.
• Establish automated testing, validation, versioning, and release processes for ML pipelines.
• Implement model and pipeline monitoring, logging, alerting, and operational dashboards.
• Develop reusable aut

📌 Data engineer II/MLOps Enginneer (India)
🏢 VARITE
📍 India