- Design and architect scalable data engineering solutions using Azure Databricks.

- Develop and optimize ETL/ELT pipelines for enterprise data processing.

- Build and maintain data lake/lakehouse solutions using Azure services.

- Develop data transformation workflows using PySpark/Scala, Python, and SQL.

- Implement Delta Lake architecture to support reliable and high-performance data processing.

- Collaborate with business and technical stakeholders to deliver robust data solutions.

- Ensure data quality, governance, security, and performance optimization.

- Implement CI/CD pipelines and follow DevOps best practices for deployment and version control.

Required Skills :

- 12+ years of experience in Data Engineering, Data Architecture, or related roles.

- Strong expertise in Azure Databricks.

- Hands-on experience with Apache Spark (PySpark/Scala).

- Proficiency in Python and SQL.

- Experience with Azure Data Factory (ADF) and Azure Data Lake Storage (ADLS).

- Strong understanding of ETL/ELT, Delta Lake, and Data Modeling.

- Experience with Git, CI/CD, and DevOps practices.

- Excellent analytical, problem-solving, and stakeholder management skills.