What are the responsibilities and job description for the MS Fabric /ADF Architect-W2 position at Singlepoint Solutions?
Job Details
Title- MS Fabric /ADF Architect
Location: New York, NY, (Onsite)
Contract (10 months 16 days)
W2 JOB DESCRIPTION:
- Deep expertise in modern data architecture, with specific experience in Microsoft's data platform and Delta Lake architecture.
- 6 years of experience in data architecture and engineering.
- Required 2 years hands-on experience with Azure Databricks / ADF and Spark.
- Required recent experience with Microsoft Fabric platform.
Key Responsibilities:
Data Architecture:
- Design end-to-end data architecture leveraging Microsoft Fabric's capabilities.
- Design data flows within the Microsoft Fabric environment.
- Implement OneLake storage strategies.
- Configure Synapse Analytics workspaces.
- Establish Power BI integration patterns.
Integration Design:
- Architect data integration patterns with analytics using Azure Data Factory and Microsoft Fabric.
- Implement medallion architecture (Bronze/Silver/Gold layers).
- Ability to configure real-time data ingestion patterns.
- Establish data quality frameworks.
Lakehouse Architecture:
- Implement modern data lakehouse 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.
- Analytics 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
Azure Databricks Experience:
- Apache 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 Databricks clusters for optimized performance. (Ex: autoscaling and automatic termination)
- Integration with Azure Services: Integrating Databricks with other Azure services like Azure Data Lake, Azure SQL Database, and Azure Synapse Analytics.
- Data Governance: Implementing data governance practices using Unity Catalog and Microsoft Purview
Security Framework:
- Design and implement security patterns aligned with federal and state requirements for sensitive data handling.
Implement row-level security.
- Configure Microsoft Purview policies.
- Establish data masking for sensitive information.
- Design audit logging mechanisms.
Pipeline Development:
- Design scalable data pipelines using Azure Databricks 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.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
