Key Responsibilities :

- Design, build, and maintain data pipelines using Azure Data Factory, Databricks, and Data Lake.

- Develop efficient, reusable, and scalable ETL/ELT processes in Python, PySpark, and SQL.

- Implement and maintain data models, transformations, and integrations for large-scale data platforms.

- Ensure data quality, governance, and security compliance in all processes.

- Collaborate with data scientists, analysts, and business teams to enable data-driven decision-making.

- Apply CI/CD practices and work with Azure DevOps for deployment and version control.

- Troubleshoot and optimize performance of data pipelines, APIs, and integrations.

- Ensure data security and compliance across platforms and services.

Technical Skills & Experience :

- 7+ years of experience in Data Engineering with strong expertise in Azure-based solutions.

- Proficiency in Python, PySpark, and SQL (including advanced queries, performance tuning).

- Hands-on experience with Azure services:

- Azure Databricks (data processing, ML model support)

- Azure Data Factory (ETL/ELT orchestration)

- Azure Data Lake (storage and data management)

- Azure DevOps (CI/CD pipelines, version control)

- Strong understanding of CI/CD principles for data workflows.

- Good knowledge of API/web service security and data security practices.

- Experience with relational databases (SQL Server, Oracle, MySQL, etc.

- Familiarity with ML libraries (added advantage).

- Excellent problem-solving, troubleshooting, and communication skills