Job
Description
Role Overview: As a highly skilled Data Architect, you will be responsible for designing, developing, and maintaining end-to-end data architecture solutions using leading-edge platforms such as Snowflake, Azure, and Azure Data Factory (ADF). Your role will involve translating complex business requirements into scalable, secure, and high-performance data solutions to enable analytics, business intelligence (BI), and machine learning (ML) initiatives. Key Responsibilities: - Design and develop end-to-end data architectures for integration, storage, processing, and analytics utilizing Snowflake and Azure services. - Build scalable, reliable, and high-performing data pipelines using Azure Data Factory (ADF) and Snowflake to handle large volumes of data. - Create and maintain data models optimized for query performance and analytics with Azure Synapse Analytics and Azure Analysis Services (AAS). - Define and implement data governance standards, data quality processes, and security protocols across all data solutions. Cloud Data Platform Management: - Architect and manage data solutions on Azure Cloud, ensuring seamless integration with services like Azure Blob Storage, Azure SQL, and Azure Synapse. - Utilize Snowflake for data warehousing to ensure high availability, scalability, and performance. - Design data lakes and data warehouses using Azure Synapse to create architecture patterns for large-scale data storage and retrieval. Data Integration & ETL Development: - Lead the design and development of ETL/ELT pipelines using Azure Data Factory (ADF) to integrate data from various sources into Snowflake and other Azure-based data stores. - Develop data transformation workflows using Python and ADF to process raw data into analytics-ready formats. - Design and implement efficient ETL strategies using Python, ADF, and Snowflake. Analytics & Business Intelligence (BI): - Design and implement data models for BI and reporting solutions using Azure Analysis Services (AAS) and Power BI. - Create efficient data pipelines and aggregation strategies to support real-time and historical reporting across the organization. - Implement best practices for data modeling to support business decision-making with tools like Power BI, AAS, and Synapse. Advanced Data Solutions (AI/ML Integration): - Collaborate with data scientists and engineers to integrate machine learning (ML) and AI models into data pipeline architecture. - Optimize the data architecture for AI-driven insights and large-scale, real-time analytics. Collaboration & Stakeholder Engagement: - Work with cross-functional teams to understand data requirements and align with business goals. - Provide technical leadership, guiding development teams and ensuring adherence to architectural standards and best practices. - Communicate complex data architecture concepts to non-technical stakeholders, translating business needs into actionable solutions. Performance & Optimization: - Continuously monitor and optimize data solutions for fast, scalable data queries, transformations, and reporting functions. - Troubleshoot and resolve performance bottlenecks in data pipelines and architecture to ensure high availability. - Implement strategies for data archiving, partitioning, and optimization in Snowflake and Azure Synapse environments. Security & Compliance: - Design and implement robust security frameworks to protect sensitive data across Snowflake, Azure Synapse, and other cloud platforms. - Ensure data privacy and compliance with industry regulations (e.g., GDPR, CCPA) through necessary security controls and access policies. Qualification Required: - Proficiency in Snowflake, Azure databricks, and Python.,
