Technology SME

• Design end-to-end enterprise data platform architectures covering data ingestion, transformation, storage, governance, and analytics layers.
• Architect scalable cloud-native data platforms using Azure services, Informatica IDMC etc.
• Define data architecture blueprints, data models, and integration frameworks aligned with enterprise data governance and security standards.
• Design and implement data lakehouse architectures enabling unified data management and analytics across structured and unstructured data.
• Develop scalable data ingestion frameworks supporting batch and real-time pipelines from multiple enterprise systems.
• Establish enterprise data integration patterns using APIs, event-based architectures, and enterprise integration tools.
• Implement enterprise data governance and metadata management frameworks using tools such as Microsoft Purview and Informatica IDMC.
• Design and implement data quality monitoring frameworks to improve reliability and consistency of enterprise data assets.
• Perform data platform sizing, capacity planning, and cost estimation by analyzing data volumes, workload patterns, storage growth, and compute requirements to ensure optimal performance and cost-efficient cloud resource utilization.
• Define data lifecycle management policies including data retention, archival, and regulatory compliance requirements.
• Design secure data platform architectures incorporating encryption, access control, identity integration, and data protection mechanisms.
• Implement data security controls including RBAC, network isolation, private endpoints, and secure data sharing mechanisms.
• Design scalable data storage strategies and performance optimization approaches for large-scale analytics workloads.
• Develop standardized data onboarding frameworks and automation pipelines for integrating new datasets and systems into the platform.
• Establish DevOps and DataOps practices including CI/CD pipelines, Infrastructure as Code, and automated deployment pipelines.
• Provide technical leadership across architecture reviews, platform design validation, and engineering implementation phases.
• Collaborate with stakeholders to define data platform roadmaps, modernization strategies, and architecture standards.
• Ensure architectural integrity, scalability, and alignment with enterprise data governance and compliance frameworks.

", "key_skills_required": "

• 8+ years of experience in data platform engineering and cloud architecture with strong Azure ecosystem exposure.
• Strong expertise in Azure data and analytics services, including Azure Data Factory (ADF) ,Azure Databricks, Azure Synapse Analytics, Microsoft Purview, Microsoft Fabric, Azure Storage and Data Lake.
• Hands-on experience with Informatica Intelligent Data Management Cloud (IDMC) including, Data integration, Data quality management, Metadata management, Data catalog and governance.
• Strong experience designing enterprise data lake and lakehouse architectures using modern big data technologies.
• Experience implementing enterprise data security frameworks, including, Role-Based Access Control (RBAC), Data encryption and key management, Identity and access management integration, Secure data access and sharing mechanisms.
• Strong experience designing scalable data platforms supporting large-scale analytics workloads.
• Experience implementing Infrastructure as Code using Terraform, ARM templates, or Bicep.
• Experience working with CI/CD pipelines using Azure DevOps or GitHub Actions.
• Strong consulting, analytical, and stakeholder management skills with the ability to translate business requirements into technical solutions.

Preferred Certifications

• Microsoft Certified: Azure Solutions Architect Expert
• Microsoft Certified: Azure Data Engineer Associate
• Azure Security or Cloud Infrastructure certifications
• Databricks Certified Data Engineer

We are looking for an experienced, hands-on Azure Technology SME to lead the architecture, design, and delivery of advanced Data and AI solutions for enterprise clients across industries. The role combines technical leadership, strategic consulting, and solution design, ensuring organizations derive measurable business value from their data investments.

The SME will act as a trusted advisor to stakeholders, guiding technical teams and designing scalable, secure, and future-ready platforms leveraging modern cloud, analytics, and artificial intelligence technologies. The role involves defining enterprise data architectures, building modern data ecosystems, and implementing AI capabilities that support advanced analytics, automation, and decision-making.

Disclaimer: This job posting and Location has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.