Key Responsibilities:

- Design, develop, and maintain scalable ETL/ELT pipelines using Azure Data Factory (ADF).
- Build and optimize data ingestion, transformation, and processing pipelines for structured and unstructured data.
- Develop scalable data solutions using Azure Databricks, Azure Data Lake Storage (ADLS), and Azure Synapse Analytics.
- Write effective and optimized SQL, Python, and PySpark code for data transformation and processing.
- Design and implement analytical data pipelines for big data and relational database environments.
- Collaborate with cross-functional teams to understand business requirements and translate them into scalable data solutions.
- Ensure data quality, performance, scalability, and reliability across the data platform.
- Monitor, troubleshoot, and optimize data workflows and processing jobs.
- Implement best practices for data engineering, security, governance, and performance optimization.




- Support deployment automation using DevOps and CI/CD pipelines.

Required Skills & Qualifications:

Must-Have Skills:

- Robust experience in Azure Data Factory (ADF) for ETL pipeline development.
- Hands-on expertise with Azure Databricks and PySpark.
- Experience working with Azure Data Lake Storage (ADLS).
- Strong knowledge of Azure Synapse Analytics and Azure SQL Database.
- Proficiency in SQL, Python, and PySpark.
- Experience building data ingestion, transformation, and analytical pipelines.
- Strong understanding of big data processing and relational database concepts.
- Experience designing scalable, high-performance data engineering solutions.
- Strong analytical, debugging, and problem-solving skills.

📌 ValueMomentum Software - Senior Data Engineer - Azure Data Factory (India)
🏢 ValueMomentum
📍 India