- Design, develop, and lead implementation of data pipelines using Azure Data Services (Azure Data Lake, Azure Data Factory, Synapse) and Databricks.

- Architect and optimize scalable ETL/ELT processes and data orchestration frameworks to meet enterprise requirements.

- Drive DevOps practices including CI/CD pipelines, Infrastructure as Code (IaC), and monitoring solutions to enable seamless deployment and operational excellence.

- Implement and manage data lineage, cataloging, and enterprise data marketplace concepts ensuring transparency and accessibility.

- Integrate and manage third-party data sources, ensuring high data quality and adherence to governance standards.

- Leverage Large Language Models (LLMs) and Copilot tools to improve productivity and automation within the data platform.

- Build self-healing architectures for data pipelines to minimize downtime and maximize reliability.

- Collaborate with cross-functional teams to implement data governance frameworks using tools like Databricks Unity Catalog.

- Lead data platform strategy with an emphasis on enterprise HR/People platforms such as Workday or ServiceNow.

Required Skills & Qualifications :

- Extensive hands-on architecting experience with Databricks, Unity Catalog, and Lakehouse architecture.

- Strong proficiency in Azure cloud services, particularly Azure Data Factory (ADF) and related data platform services.

- Proven track record of building and optimizing complex data pipelines in large-scale enterprise environments.

- Experience with enterprise HR implementations and data integrations, preferably with Workday, ServiceNow, or similar platforms.

- Deep understanding of data governance frameworks, data quality best practices, and metadata management.

- Expertise in scripting languages for automation and orchestration within the data platform ecosystem.

- Strong problem-solving skills and ability to work collaboratively across teams and stakeholders.

- Excellent communication and leadership capabilities.