Description

Design and build scalable data and AI platforms to support analytics, machine learning, and generative AI solutions.

This role is on-site.

Responsibilities

• Architect cloud-native data platforms using Azure, AWS, or GCP.
• Develop and maintain ETL/ELT pipelines and data integration frameworks.
• Build data lakes, warehouses, and real-time streaming solutions.
• Deploy AI/ML models into production and implement MLOps/DataOps practices.
• Define data governance, security, and privacy standards.

Required Skills

• 8+ years of experience in Data Engineering and Data Architecture.
• Strong proficiency in Python, SQL, Spark, and Databricks.
• Hands-on experience with Airflow or Azure Data Factory for orchestration.
• Expertise in building robust ETL/ELT processes.
• Demonstrated experience with Azure, AWS, or GCP cloud platforms.
• Knowledge of data lakes, data warehouses, and big data technologies.
• Understanding of APIs, microservices, and containerization (Docker, Kubernetes).

Preferred Skills

• Experience with Machine Learning, Generative AI, and MLOps.
• Knowledge of network routing (WAN) and switching (LAN) technologies.

Key Skills

Education

Any Graduate