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Responsibilities: 

Experience: We are seeking an experienced Azure Data Architect with strong expertise in designing, architecting, and implementing enterprise-scale data platforms on Microsoft Azure. The ideal candidate will play a strategic role in defining modern data architecture, enabling scalable, secure, and future-ready data solutions, and driving data transformation initiatives for clients across industries. In this role, you will work closely with business stakeholders, engineering teams, analysts, and leadership to deliver cloud-native data platforms, analytics solutions, governance frameworks, and AI-enabled data ecosystems aligned with business goals. 

- Collaborate with business stakeholders, solution teams, and clients to understand data requirements and translate them into scalable Azure-based data architecture solutions. 
- Design and implement modern data platforms on Azure using services such as Azure Data Factory, Azure Synapse Analytics, Azure Data Lake Storage, Azure Databricks, Azure SQL, and Microsoft Fabric where applicable. 
- Define end-to-end data architecture including ingestion, transformation, storage, semantic modeling, data serving, security, and monitoring. 
- Create architecture blueprints, data models, solution design documents, and implementation roadmaps aligned to enterprise data strategy. 
- Design batch and real-time data pipelines for structured, semi-structured, and unstructured data sources. 
- Lead data migration and modernization initiatives from on-premise or legacy platforms to Azure cloud. 
- Establish best practices for data governance, master data management, metadata management, data lineage, and data quality. 
- Ensure security, privacy, and compliance requirements are embedded in data solutions, including role-based access control, encryption, and regulatory adherence. 
- Partner with engineering and DevOps teams to enable CI/CD, infrastructure as code, automation, and environment standardization for data platforms. 
- Provide architectural guidance on performance optimization, cost optimization, scalability, disaster recovery, and high availability. 
- Support analytics and reporting use cases by enabling curated data layers for BI tools such as Power BI and enterprise reporting platforms. 
- Review solution designs and code artifacts to ensure alignment with architectural standards and industry best practices. 
- Lead technical discussions, architecture governance forums, and client workshops to drive decision-making and stakeholder alignment. 
- Mentor data engineers, analysts, and technical teams on Azure architecture patterns, implementation standards, and modern data engineering practices. 
- Monitor project progress, identify architecture risks/issues, and provide mitigation strategies to ensure successful delivery. 
- Continuously evaluate emerging Azure data services and recommend innovations to improve platform capability and business value. 
- Apply working knowledge of Generative AI tools and AI-assisted productivity platforms to improve solution design, documentation, code acceleration, data discovery, and delivery efficiency. 
- Identify appropriate use cases for Gen AI within data platforms, including intelligent search, natural language-based analytics, knowledge retrieval, document processing, and AI-assisted reporting. 
- Guide teams on the effective and responsible use of Gen AI tools for architecture documentation, code generation support, query optimization, and productivity enhancement while maintaining quality, security, and compliance standards. 

Mandatory skill sets: 

- Strong understanding of enterprise data architecture, cloud data platforms, data modeling, and analytics ecosystems. 
- 8+ years of experience in data architecture, data engineering, or related roles, with significant hands-on experience in Azure data services. 
- Proven experience in designing and implementing large-scale cloud data platforms and analytics solutions on Microsoft Azure. 
- Strong experience with Azure services such as Azure Data Factory, Azure Synapse, Azure Databricks, ADLS Gen2, Azure SQL Database, Microsoft Fabric, and Power BI. 
- Experience with data warehousing, lakehouse architecture,data mesh, dimensional modeling, and modern ELT/ETL frameworks. 
- Good understanding of data governance, security, privacy, and compliance principles in enterprise environments. 

Preferred skill sets: 

- Strong hands-on experience with Azure Databricks, Spark, big data,Azure Data Factory, Azure Synapse Analytics, Azure SQL, Azure Data Lake Storage Gen2, Event Hub, Stream Analytics, and Microsoft Fabric. 
- Proficiency in SQL, Python, PySpark, and data transformation frameworks. 
- Experience in designing data lakes, lakehouse platforms, enterprise data warehouses, and real-time streaming solutions. 
- Knowledge of data integration patterns, API-based ingestion, CDC, and orchestration frameworks. 
- Experience with BI and visualization tools such as Power BI and Tableau. 
- Working knowledge of DevOps, CI/CD pipelines, Infrastructure as Code (ARM/Bicep/Terraform), and version control tools like Git. 

Years of experience required: 

8-14 Years 

Education qualification: 

B.Tech/B.E.