Data Engineer

Azure Databricks Engineer

Location

(Relocation is not supported)

Work Mode

Compensation

🧪 Interview Process

• 2 Virtual Interview Rounds

Role Overview :-

Azure Databricks Engineer

🎯 Key Responsibilities

• Design, develop, and optimize

  ETL pipelines

  using

  Azure Databricks and PySpark

• Build and maintain scalable data processing workflows on

  Azure Cloud

• Develop data ingestion and transformation pipelines using

  Azure Data Factory (ADF)

• Optimize Spark jobs for performance, scalability, and cost efficiency
• Work with structured and semi-structured data sources
• Implement data quality checks, monitoring, and error handling
• Collaborate with data architects, analysts, and stakeholders to understand data requirements
• Ensure security, compliance, and best practices across Azure data platforms
• Troubleshoot and resolve production data pipeline issues

🛠 Required Skills & Qualifications

• 7+ years

  of overall experience in Data Engineering / ETL Development

• Minimum 5 years of hands-on experience with Azure Databricks

• Strong proficiency in

  Python & PySpark

• Solid experience with

  Azure Data Factory (ADF)

• Strong SQL skills for data transformation and analysis
• Experience working with large-scale data processing systems
• Strong understanding of

  ETL/ELT concepts and data warehousing

• Experience with Azure services such as

  ADLS, Azure SQL, Synapse

  (good to have)
• Excellent problem-solving and communication skills

🌟 Nice to Have

• Experience with performance tuning and cost optimization in Databricks
• Exposure to CI/CD for data pipelines
• Experience working in Agile environments