Description

Job Responsibilities include:

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

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.

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 Qualifications:

Bachelor’s degree in computer science (required), Data Engineering, Information Technology, or a related technical discipline.

8–10 years of experience in Data Architecture, Data Engineering, Cloud Data Platforms, or Enterprise Analytics, including 3+ years focused on Cloud Data Architecture.

Strong expertise in Azure Data Lake, Azure Data Factory, Synapse Analytics, Databricks, Spark, Python, SQL, data modeling, metadata management, and cloud-native data architecture design.

Proven experience implementing scalable data lakehouse and data warehouse solutions, data governance frameworks, metadata/catalog tools (Purview, Unity Catalog, Collibra), and enterprise data integration solutions supporting analytics and AI initiatives

Key Skills

Education

Any Graduate