Description

You will design, architect, and optimize cloud-based data lakehouse and data warehouse solutions using Azure technologies to support enterprise analytics, reporting, and AI initiatives. You will develop scalable data architecture frameworks for ingestion, transformation, storage, governance, and consumption across large-scale cloud environments. This role is on-site.

Responsibilities

• Lead metadata management, data lineage, and governance initiatives using Purview, Unity Catalog, or similar platforms to improve data quality and discoverability.
• Collaborate with data engineers, business stakeholders, and cloud teams to translate business requirements into secure, scalable, and high-performance data solutions.
• Build and support distributed data processing solutions using Databricks, Spark, Python, and SQL while driving performance, scalability, and cost optimization.
• Create and maintain architecture documentation, data models, system diagrams, and technical standards while ensuring compliance with enterprise data governance and security requirements.

Required Skills

• 8–10 years of experience in Data Architecture, Data Engineering, Cloud Data Platforms, or Enterprise Analytics.
• 3+ years of focused experience in Cloud Data Architecture.
• Strong expertise in Azure Data Lake, Azure Data Factory, Synapse Analytics, Databricks, Spark, Python, and SQL.
• Proven experience implementing scalable data lakehouse and data warehouse solutions.
• Experience with data governance frameworks and metadata/catalog tools such as Purview, Unity Catalog, or Collibra.
• Proficiency in data modeling and cloud-native data architecture design.
• Knowledge of enterprise data integration solutions supporting analytics and AI initiatives.

Key Skills

Education

Any Graduate