Data Architect

Designing robust and scalable data architectures leveraging Azure and AWS services, encompassing data lakes, warehouses, pipelines, and streaming solutions.
Demonstrating deep understanding of Azure and AWS platforms, including storage (Azure Blob Storage, AWS S3), compute (Azure VMs, AWS EC2), databases (Azure SQL Database, AWS RDS), and big data processing (Azure Databricks, AWS EMR).
Integrating data from diverse sources into cloud environments using tools like Azure Data Factory, AWS Glue, or custom ETL processes.
Ensuring data solutions comply with industry standards like GDPR, implementing security best practices, encryption, and access controls.
Optimizing data pipelines, queries, and storage for performance and cost-efficiency, monitoring and tuning to meet SLAs and business requirements.
Implementing disaster recovery, backup, and high availability strategies for data resilience and business continuity.
Documenting architecture designs, configurations, and best practices for Azure and AWS data solutions, providing guidance on implementation.
Implementing data cataloging and metadata management for proper documentation and discoverability.
Performance Optimization: Optimizing data pipelines, queries, and analytics performance for MicroStrategy dashboards and reports.
Ensuring security compliance on Azure and AWS, implementing encryption, access controls, and auditing mechanisms.
Optimizing data storage and processing costs, monitoring resource usage for efficiency.
Implementing data backup and disaster recovery strategies for data availability and business continuity.
Designing logical and physical data models for SQL Server databases, ensuring integrity, normalization, and performance.
Collaborating with cross-functional teams to understand data integration needs and provide tailored solutions.
Required Skills:

Proven experience as a Data Architect or Data Engineer with hands-on experience in designing and implementing data solutions on Azure Data Lake and AWS.
Strong understanding of cloud services and data architecture principles.
Proficiency in data integration and ETL concepts and practical experience with cloud technologies.
Knowledge of data storage and processing technologies in Azure, including Azure Data Lake Storage, Azure Data Lake Analytics, and Azure Synapse Analytics and legacy SQL Data Warehouse.
Experience in migration projects from On Prem to Azure Cloud Services (Data Lake/Synapse).
Experience with data transformation and data preparation tools and techniques.
Knowledge of data security and compliance practices in the Azure cloud environment.
Familiarity with data cataloging and metadata management tools and practices.
Azure certifications related to data and analytics (e.g., Microsoft Certified: Azure Data Engineer Associate) are a plus.
In-depth knowledge of SQL Server database design, implementation, and administration.
Proficiency in SQL programming, T-SQL, and stored procedures.
Familiarity with data warehousing and business intelligence concepts.