ADF Data Engineer / L3 Support

• Incident classification and prioritization
  
• Log analysis and trend identification
  
• Coordination with Subject Matter Experts (SMEs)
  
• Escalation of unresolved or complex issues
  
• Root cause analysis and permanent resolution implementation
  
• Stakeholder communication and status updates
  
• Resolution of complex and major incidents
  
• Code reviews (Per week 2 per individual) to ensure adherence to standards and optimize performance
  
• Bug fixing of recurring or critical issues identified during operations
  
• Gold layer tasks, including enhancements and performance tuning.

Design, develop, and support data pipelines and solutions using Azure data engineering services.

Implement data flow and ETL techniques leveraging Azure Data Factory, Databricks, and Synapse.

Cleanse, transform, and enrich datasets using Databricks notebooks and PySpark.

Orchestrate and automate workflows across services and systems.

Collaborate with business and technical teams to deliver robust and scalable data solutions.

Work in a support role to resolve incidents, handle change/service requests, and monitor performance.

Contribute to CI/CD pipeline implementation using Azure DevOps.

Technical Requirements:

3 to 6 years of experience in IT and Azure data engineering technologies.

Strong experience in Azure Databricks, Azure Synapse, and ADLS Gen2.

Proficient in Python, PySpark, and SQL.

Experience with file formats such as JSON and Parquet.

Working knowledge of database systems, with a preference for Teradata and Snowflake.

Hands-on experience with Azure DevOps and CI/CD pipeline deployments.

Understanding of Data Warehousing concepts and data modeling best practices.

Familiarity with SNOW (ServiceNow) for incident and change management.

Non-Technical Requirements:

Ability to work independently and collaboratively in virtual teams across geographies.

Strong analytical and problem-solving skills.

Experience in Agile development practices, including estimation, testing, and deployment.

Effective task and time management with the ability to prioritize under pressure.

Clear communication and documentation skills for project updates and technical processes.

Technologies:

Azure Data Factory

Azure Databricks

Azure Synapse Analytics

PySpark / SQL

Azure Data Lake Storage (ADLS), Blob Storage

Azure DevOps (CI/CD pipelines)

Nice-to-Have:

Experience with Business Intelligence tools, preferably Power BI

DP-203 certification (Azure Data Engineer Associate)