Azure Data Engineer
Syntricate Technologies
Azure Data Engineer
Dallas TX (Hybrid 3 days in a week)
12+ Months
Web Cam Interview Requirement Notes (Candidate Job description below) :
Experience required on a resume and for submittal:
Education:
Programming & Tools:
Data Pipeline Development:
Dallas TX (Hybrid 3 days in a week)
12+ Months
Web Cam Interview Requirement Notes (Candidate Job description below) :
- We need a senior (10+ years) Azure Data engineer with recent experience in Banking, Capital Markets or Financial services.
- Candidates must have recent experience working with Azure Data Factory (ADF) and Azure Databricks in a Financial environment.
- Candidates must have excellent communication skills/no accent.
Experience required on a resume and for submittal:
- How many years working with: Azure Data Engineer
- How many years working with: Azure Data Factory (ADF)
- How many years working with: Azure Databricks (highlighted expertise)
- How many years working with: Banking, Capital Markets or Financial services OR FORTUNE 500
Education:
- Bachelor's or Master's degree in Computer Science, Information Technology, or a related field (Engineering or Math preferred).
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.
- Microsoft Certified: Azure Data Engineer Associate
- Databricks Certified Data Engineer Associate or Professional
- 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.
Data Pipeline Development:
- Create and manage scalable data pipelines to collect, process, and store large volumes of data from various sources.
- Integrate data from multiple sources, ensuring consistency, quality, and reliability.
- Design, implement, and optimize database schemas and structures to support data storage and retrieval.
- Develop and maintain ETL (Extract, Transform, Load) processes to ensure accurate and efficient data movement between systems.
- Build and maintain data warehouses to support business intelligence and analytics needs.
- Optimize data processing and storage performance for efficient resource utilization and quick data retrieval.
- Create and maintain comprehensive documentation for data pipelines, ETL processes, and database schemas.
- Monitor data pipelines and systems for performance and reliability, troubleshooting and resolving issues as they arise.
- Stay updated with emerging technologies and best practices in data engineering, evaluating and recommending new tools and technologies as appropriate.
Vacancy posted 1 day ago
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