Description

Design, architect, and optimize cloud-based data lakehouse and data warehouse solutions using Azure technologies to support enterprise analytics and AI initiatives.

This role is on-site.

Responsibilities

• Develop scalable data architecture frameworks for data ingestion, transformation, storage, governance, and consumption across large-scale cloud environments.
• Lead metadata management, data lineage, and governance initiatives using tools such as Purview, Unity Catalog, or similar platforms to improve data quality and discoverability.
• Build and support distributed data processing solutions using Databricks, Spark, Python, and SQL while driving performance, scalability, and cost optimization.
• Collaborate with data engineers, business stakeholders, and cloud teams to translate business requirements into secure, scalable data solutions.
• Create and maintain architecture documentation, data models, system diagrams, and technical standards ensuring compliance with enterprise data governance.

Required Skills

• 8–10 years of experience in Data Architecture, Data Engineering, Cloud Data Platforms, or Enterprise Analytics.
• 3+ years focused specifically on Cloud Data Architecture.
• Strong expertise in Azure Data Lake, Azure Data Factory, Synapse Analytics, and Databricks.
• Proficiency in Spark, Python, and SQL for distributed data processing.
• Proven experience implementing scalable data lakehouse and data warehouse solutions.
• Experience with data governance frameworks and metadata/catalog tools (Purview, Unity Catalog, Collibra).
• Bachelor’s degree in computer science, Data Engineering, Information Technology, or a related technical discipline.

Key Skills

Education

Any Graduate