Description

You will design and architect scalable AI and data platforms to support analytics, machine learning, and GenAI use cases. This role focuses on building robust data pipelines, ETL/ELT processes, and integration frameworks while ensuring data governance and security standards.

This role is on-site.

Responsibilities

• Develop and maintain data pipelines, lakes, warehouses, and real-time streaming solutions.
• Collaborate with data scientists and ML engineers to deploy models into production.
• Architect cloud-native solutions using Azure, AWS, or GCP.
• Implement MLOps and DataOps best practices to optimize performance and cost.
• Define data governance, security, privacy, and compliance standards.

Required Skills

• 10+ years of experience in Data Engineering and Data Architecture.
• Strong proficiency in Python, SQL, Spark, and Databricks.
• Hands-on experience with cloud platforms (Azure, AWS, or GCP).
• Experience with orchestration tools such as Airflow or Azure Data Factory.
• Knowledge of containerization technologies (Docker, Kubernetes) and APIs.
• Understanding of data lakes, big data technologies, and MLOps.
• Bachelor's degree in a relevant field.

Preferred Skills

• Experience with Generative AI technologies and tools.
• Background in network routing (WAN) and switching (LAN) technologies.
• Project management experience.

Key Skills

Education

Bachelor's degree