Description

You will define enterprise data architecture and platform patterns for lakehouse and modern data environments. You will architect end-to-end data engineering solutions and drive technical discussions with stakeholders.

This role is on-site.

Responsibilities

• Define enterprise data architecture and data platform patterns for lakehouse and modern data architectures.
• Develop and maintain conceptual and logical data models aligned to enterprise standards and analytics needs.
• Architect end-to-end data engineering solutions using Azure Databricks and PySpark for distributed processing.
• Drive architecture discussions with business and technology stakeholders, translating requirements into scalable data designs.
• Support advanced analytics and AI enablement by ensuring data models and platform capabilities meet enterprise scalability requirements.

Required Skills

• 10+ years of experience in data engineering, analytics, and enterprise data architecture.
• Strong expertise in enterprise data architecture and architecture standards.
• Expertise in conceptual data modelling and logical data modelling for enterprise-scale use cases.
• Hands-on experience with Azure Databricks and PySpark for distributed data processing.
• Experience with DevSecOps, CI/CD, and data platform delivery practices.
• Proficiency in Data Governance, Metadata management, and Master Data concepts.
• Bachelor's degree in Computer Science or related field.

Preferred Skills

• DAMA certification and experience with data governance and metadata management.
• Exposure to GenAI, LLMs, and advanced analytics enablement.

Key Skills

Education

Any Graduate