Azure Data Engineer
RIT Solutions
Senior Azure Data Analyst
A senior Azure Data Analyst with extensive experience working with the Azure Data suite listed below. The client would like to see certifications.
Candidates must have recent capital markets/trading and/or hedge fund experience and excellent communication skills. Hot & moving fast!! Candidate must have's on a resume and for submittal:
- How many years working with: Azure Data Analyst
- How many years working with: Azure Data Factory (ADF)
- How many years working with: Azure Databricks (highlighted expertise)
- How many years working with: Logic Apps
- How many years working with: Capital Markets/Hedge Funds
- Technical Skills:
- Programming & Tools: 10+ years of experience in SQL, Python..Net is a plus.
- 5+ years of experience in Azure cloud services, including:
- Azure SQL Server
- Azure Data Factory (ADF)
- Azure Databricks (highlighted expertise)
- Azure Data Lake Storage (ADLS)
- Azure Key Vault
- Azure Functions
- Logic Apps
- 5+ years of experience in GIT and deploying code using CI/CD pipelines.
- Certifications (Preferred):
- Microsoft Certified: Azure Data Engineer Associate
- Databricks Certified Data Engineer Associate or Professional
Responsibilities:
- Data Pipeline Development: Create and manage scalable data pipelines to collect, process, and store large volumes of data from various sources.
- Data Integration: Integrate data from multiple sources, ensuring consistency, quality, and reliability.
- Database Management: Design, implement, and optimize database schemas and structures to support data storage and retrieval.
- ETL Processes: Develop and maintain ETL (Extract, Transform, Load) processes to ensure accurate and efficient data movement between systems.
- Data Warehousing: Build and maintain data warehouses to support business intelligence and analytics needs.
- Performance Optimization: Optimize data processing and storage performance for efficient resource utilization and quick data retrieval.
- Documentation: Create and maintain comprehensive documentation for data pipelines, ETL processes, and database schemas.
- Monitoring and Troubleshooting: Monitor data pipelines and systems for performance and reliability, troubleshooting and resolving issues as they arise.
- Technology Evaluation: Stay updated with emerging technologies and best practices in data engineering, evaluating and recommending.
Vacancy posted 4 days ago
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