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What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- Strong understanding of Data Engineering concepts and ETL/ELT frameworks
- Hands-on experience with SQL and database technologies
- Exposure to Azure Data Engineering services including Azure Databricks Azure Data Factory and Azure SQL or Synapse
- Knowledge of Python or PySpark for data processing and automation
- Experience with DevOps and CI/CD tools such as Azure DevOps Jenkins GitHub Actions and Git
- Understanding of cloud platforms preferably Microsoft Azure
- Familiarity with monitoring logging and operational support processes
- Basic understanding of APIs scripting and automation
- Exposure to containerization technologies like Docker and Kubernetes
- Experience with Data Quality validation and monitoring frameworks
- Familiarity with Infrastructure-as-Code tools such as Terraform or ARM templates
- Knowledge of Agile delivery methodologies
- Understanding of cloud security and governance practices
Nice to have
- Analytical
- Collaborative
- Detail-oriented
- Problem-solving
- Adaptable
Day to day
- Design, develop, and maintain scalable ETL/ELT pipelines for enterprise data platforms
- Build and optimize data ingestion transformation and integration workflows across cloud and enterprise systems
- Support digital operations by monitoring data pipelines troubleshooting incidents and improving platform reliability
- Automate deployments and operational processes while collaborating with engineering analytics and infrastructure teams