We are seeking a highly skilled Data Architect to design, develop, and maintain end-to-end data architecture solutions, leveraging leading-edge platforms such as Snowflake, Azure, and Azure Data Factory (ADF). The role involves translating complex business requirements into scalable, secure, and high-performance data solutions while enabling analytics, business intelligence (BI), and machine learning (ML) initiatives.

Key Responsibilities:

Data Architecture & Design:

Design and develop end-to-end data architectures for integration, storage, processing, and analytics using Snowflake and Azure services. Build scalable, reliable, and high-performing data pipelines to handle large volumes of data, utilizing Azure Data Factory (ADF) and Snowflake. Create and maintain data models (dimensional and relational) optimized for query performance and analytics using 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. Leverage Snowflake for data warehousing to ensure high availability, scalability, and performance. Design data lakes and data warehouses using Azure Synapse, creating 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 a combination of 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. Ensure that the data architecture is optimized for AI-driven insights and large-scale, real-time analytics.

Collaboration & Stakeholder Engagement:

Work with cross-functional teams, including business analysts, data engineers, data scientists, and IT 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. Effectively communicate complex data architecture concepts to non-technical stakeholders, translating business needs into actionable solutions.

Performance & Optimization:

Continuously monitor and optimize data solutions, ensuring fast, scalable data queries, transformations, and reporting functions. Troubleshoot and resolve performance bottlenecks in data pipelines and architecture, ensuring minimal downtime and 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.