Description

Key Skills: Pyspark, Data Modelling, Azure Databricks, Data Engineering, Enterprise AI architect, Analytics, DevSecOps, Data Governance, Metadata, LLM, Gen AI, Certification, CICD, Master Data

Roles and 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.

Skills Required:

• 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.

Good to Have:

• DAMA certification and experience with data governance, metadata management, and master data concepts.
• GenAI/LLM exposure and familiarity with CI/CD and DevOps practices for data platform delivery.

Education: Bachelor's degree in Computer Science or related field; Master's degree in Computer Science or related field preferred

Key Skills

Education

Any Graduate