Azure Fabric Data Architect

2 weeks ago

Newark, NJ, United States Cynet Systems Full time
Job Description:

Pay Range: $75hr - $80hr

Responsibilities:

Data Architecture:
  • Design end-to-end data architecture leveraging Microsoft Fabric's capabilities.
  • Design data flows within the Microsoft Fabric environment.
  • Implement One Lake storage strategies.
  • Configure Synapse Analytics workspaces Establish Power BI integration patterns.
Integration Design:
  • rchitect data integration patterns with analytics using Azure Data Factory and Microsoft Fabric.
  • Implement medallion architecture (Bronze/Silver/Gold layers).
  • bility to configure real-time data ingestion patterns.
  • stablish data quality frameworks.
Lakehouse Architecture:
  • Implement modern data lake house architecture using Delta Lake, ensuring data reliability and performance.
Data Governance:
  • Establish data governance frameworks incorporating Microsoft Purview for data quality, lineage, and compliance.
Microsoft Fabric Expertise:
  • Data Integration: Combining and cleansing data from various sources.
  • Data Pipeline Management: Creating, orchestrating, and troubleshooting data pipelines.
  • nalytics Reporting: Building and delivering detailed reports and dashboards to derive meaningful insights from large datasets.
  • Data Visualization Techniques: Representing data graphically in impactful and informative ways.
  • Optimization and Security: Optimizing queries, improving performance, and securing data.
zure Databricks Experience:
  • pache Spark Proficiency: Utilizing Spark for large-scale data processing and analytics.
  • Data Engineering: Building and managing data pipelines, including ETL (Extract, Transform, Load) processes.
  • Delta Lake: Implementing Delta Lake for data versioning, ACID transactions, and schema enforcement.
  • Cluster Management: Configuring and managing Data bricks clusters for optimized performance.
  • Integration with Azure Services: Integrating Data bricks with other Azure services like Azure Data Lake, Azure SQL Database, and Azure Synapse Analytics.
  • Configure Microsoft Purview policies.
  • Establish data masking for sensitive information.
  • Design audit logging mechanisms.
Pipeline Development:
  • Design scalable data pipelines using Azure Data bricks for ETL/ELT processes and real-time data integration.
Performance Optimization:
  • Implement performance tuning strategies for large-scale data processing and analytics workloads.
  • Optimize Spark configurations.
  • Implement partitioning strategies
  • Design caching mechanisms.
  • Establish monitoring frameworks.

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