Description

Responsibilities include:

Architect and implement enterprise-scale data platforms using Databricks Lakehouse, Delta Lake, Unity Catalog, and Spark technologies.

Design and optimize batch, streaming, and real-time data integration solutions across multiple enterprise systems.

Lead cloud modernization and migration initiatives from legacy data warehouses and on-premises platforms to Azure and AWS environments.

Establish and enforce data governance, security, metadata management, and compliance standards across the data ecosystem.

Provide technical leadership, conduct architecture reviews, and mentor engineering teams on best practices and scalable solutions.

Collaborate with business and technology stakeholders to develop analytics, AI/ML, and GenAI-ready data platforms that support strategic business objectives.

Required Qualifications:

Bachelor’s or master’s degree in computer science, Information Technology, Engineering, or a related technical discipline.

10+ years of experience in data engineering, data architecture, cloud transformation, and enterprise data platform delivery.

Strong expertise in Databricks, Apache Spark/PySpark, Azure, AWS, data warehousing, and large-scale data integration solutions.

Proven experience designing and implementing enterprise Lakehouse architectures, cloud modernization programs, and real-time data processing frameworks.

Key Skills

Education

Any Graduate