Fabric Data Architect_96770
MyCareernet
2 - 5 years
Hyderabad
Posted: 21/03/2026
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Job Description
Company:IT Services Organization
Key Skills: Pyspark, Microsoft fabric, Data architecture, Azure, Python, Azure SQL, Azure Synapse, Azure Databricks, Azure Data lake, Data modeling, Power BI, Compliance, Cloud Data Governance and Catalog
Roles and Responsibilities:
- Design and implement data architecture solutions using Microsoft Fabric and Azure technologies.
- Develop and manage Fabric Lakehouse architecture including data pipelines and analytics models.
- Collaborate with cross-functional teams to integrate data platforms with Power BI and other analytics tools.
- Ensure data governance, security, compliance, and data lineage across the data ecosystem.
- Lead data modeling efforts including dimensional and lakehouse-based models.
- Provide technical leadership and mentorship to data engineers and architects.
- Optimize data processing, storage, and analytics performance across cloud platforms.
- Stay updated with industry trends and best practices in data architecture and cloud technologies.
Skills Required:
- Strong experience in Microsoft Fabric for building modern data platforms and lakehouse architectures.
- Expertise in Azure cloud services including Azure SQL for data storage and management.
- Proficiency in Python and PySpark for large-scale data processing and transformation.
- Strong understanding of data architecture principles and enterprise data platform design.
- Experience in data modeling including dimensional modeling and lakehouse architectures.
- Knowledge of Azure Data Lake for managing structured and unstructured data.
- Familiarity with Azure Synapse and Azure Databricks for advanced analytics and big data processing.
- Experience integrating Power BI for reporting and visualization.
- Strong understanding of cloud data governance, compliance, and data cataloging frameworks.
- Ability to lead and mentor teams while driving architectural best practices.
Education: Bachelor's or Master's degree in Computer Science, Information Technology, Data Engineering, or a related field.
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