Azure Data Engineer/Azure
Azure Data Engineer/Azure
Employer Active
Job Alert
You will be updated with latest job alerts via email
Share
Job Alert
You will be updated with latest job alerts via email
Job Description
Job Title: Azure Data Engineer/Azure
Client: Capital Markets/Hedge Fund
Location: Hybrid/Dallas TX NYC
Duration: 1 year
Interview: Video
Job Description:
Senior Data Engineer
Education:
Bachelors or Masters degree in Computer Science Information Technology or a related field (Engineering or Math preferred).
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
Soft Skills:
Strong analytical and problemsolving skills.
Excellent communication and interpersonal skills.
Ability to work independently and collaboratively within a team.
Attention to detail and a commitment to delivering highquality work.
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 new tools and technologies as appropriate.
Employment Type
Full Time
