- Develop and enforce comprehensive data governance frameworks to maintain data integrity, security, and regulatory compliance across the organization.

- Architect complex data models that align with business logic, enabling scalable and intuitive reporting structures for end users.

- Integrate Microsoft Fabric components to streamline data movement, transformation, and storage, reducing technical debt and operational overhead.

Required Skillset :

- Demonstrated expertise in designing large-scale data architectures using cloud-native technologies, specifically within the Azure ecosystem.

- Deep hands-on experience with Snowflake DB and Azure Databricks, including performance tuning and cost-optimization strategies.

- Strong understanding of data modeling methodologies and data governance principles, with the ability to implement policies that balance accessibility with security.

Education : Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, or a related field with 14- 18 years in data engineering/architecture, including at least 3- 5 years in an architecture or leadership capacity and demonstrable enterprise delivery ownership.

- Domain : Experience in process manufacturing / chemicals / oil & gas is strongly preferred, with exposure to plant operations and industrial data contexts.

- Platforms : Strong experience in at least one modern data platform ecosystem (Databricks, Snowflake, Microsoft Fabric) and cloud deployment practices.

- Engineering : Proven capability in designing secure, scalable pipelines and data models supporting analytics and AI; familiarity with DataOps/DevOps practices.