Azure Data Engineer
1 week ago
Overview:
We are looking for an experienced Azure Data Engineer with strong expertise in designing, developing, and optimizing data pipelines and analytics solutions on Azure. The ideal candidate will have hands-on experience in Azure Databricks, PySpark, and other Azure data services, along with strong programming and SQL skills. Basic knowledge of the Telecom domain is preferred.
Responsibilities:
Key Responsibilities:
- Design, develop, and maintain scalable data pipelines and ETL workflows using Azure Databricks and PySpark.
- Integrate and transform data from multiple sources using APIs, SQL, and Azure data storage services (e.g., Blob Storage).
- Implement data quality, validation, and monitoring frameworks for reliable data processing.
- Work with GIS (Geographic Information Systems) datasets to support location-based analytics.
- Develop automation scripts using Python and Unix shell scripting for efficient data handling.
- Collaborate with business analysts, architects, and stakeholders to gather requirements and deliver data solutions.
- Optimize workflows for performance, scalability, and cost-efficiency within Azure.
- Troubleshoot and resolve data pipeline issues promptly.
Requirements:
Required Skills & Qualifications:
- Minimum 7 years of overall IT experience, with strong data engineering expertise.
- Proficiency in Azure Databricks, PySpark, Python, and SQL.
- Experience with ETL processes, workflows, and API integrations.
- Knowledge of GIS data handling and related tools.
- Hands-on experience with Azure Blob Storage and Unix shell scripting.
- Understanding of Azure Data Services and cloud-based architecture.
- Basic understanding of the Telecom domain (network data, customer data, location-based analytics, etc.).
Nice-to-Have:
- Experience with Azure Data Factory or other orchestration tools.
- Familiarity with data security, governance, and compliance in cloud environments.
- Exposure to machine learning or data science workflows on Azure.
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