À propos
Senior Data Engineer Dallas 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. 3 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
3 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 problem-solving skills. Excellent communication and interpersonal skills. Ability to work independently and collaboratively within a team. Attention to detail and a commitment to delivering high-quality 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.
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Compétences linguistiques
- English
Avis aux utilisateurs
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