Description

• Results-driven Data Solutions Architect with extensive experience designing, architecting, and implementing enterprise-scale data platforms across Azure, AWS, and multi-cloud environments.
• Proven expertise in modern data architectures, Lakehouse implementations, cloud migrations, data modernization initiatives, and analytics platforms that enable organizations to leverage data as a strategic asset.
• Specialized in architecting end-to-end data ecosystems utilizing technologies including Azure Databricks, Azure Data Factory, ADLS Gen2, Azure Synapse Analytics, Snowflake, Kafka, Power BI, AWS Glue, Lambda, and Terraform. Experienced in designing scalable and secure data platforms capable of processing large-scale structured and unstructured datasets while ensuring performance, governance, reliability, and cost optimization.
• Strong background in defining enterprise data strategies, establishing architecture standards, and leading the delivery of cloud-native solutions that support reporting, business intelligence, advanced analytics, and AI/ML initiatives. Experienced in designing Lakehouse and Data Warehouse architectures, implementing dimensional models, and developing scalable ingestion frameworks that support both batch and real-time data processing.
• Expert in architecting high-performance data pipelines using PySpark, Databricks, Airflow, Kafka, and cloud-native services, with deep knowledge of performance optimization techniques including partitioning strategies, clustering, data skew remediation, schema evolution, workload tuning, and distributed processing best practices.
• Experienced in establishing data governance, quality, security, and compliance frameworks through automated monitoring, metadata management, schema management, and data validation processes. Adept at designing resilient architectures that support changing business requirements while maintaining scalability and operational excellence.
• Possesses extensive experience integrating analytics and business intelligence solutions through Power BI and modern reporting platforms, enabling executive leadership and business stakeholders to make informed, data-driven decisions.
• Additional expertise includes Infrastructure as Code, DevOps automation, CI/CD implementation, cloud security, and multi-cloud integration strategies. Proven ability to collaborate with engineering, analytics, business, and executive stakeholders to align technology solutions with organizational objectives and digital transformation initiatives.
• Needs to be proactive and not reactive

Core Competencies: Key requirements highlighted.
• Enterprise Data Architecture
• Azure Data Architecture( Certified )
• Databricks Architecture
• Lakehouse & Data Warehouse Design
• Cloud Data Platform Strategy
• Azure Synapse Analytics
• Azure Data Factory (ADF)
• Azure Data Lake Storage (ADLS Gen2)
• Snowflake
• PySpark & Distributed Data Processing
• Data Modeling (Star & Snowflake Schema)
• Data Governance & Data Quality
• Real-Time Data Streaming
• Kafka Architecture
• AWS Data Services
• Terraform & Infrastructure as Code
• Azure DevOps & CI/CD
• Power BI & Enterprise Analytics
• Multi-Cloud Architecture
• Data Migration & Modernization
• AI/ML Data Enablement
• Performance Optimization & Scalability

Key Skills

Education

Bachelor's degree